For those who do not know the tool, RealityScan is Epic’s photogrammetry application for reconstructing 3D assets, scenes, and datasets from photographs and scans. It is used in areas such as VFX, game development, visualization, heritage capture, and geospatial workflows. RealityScan 2.1, the previous major release, added broader automation options, support for SLAM data, and other workflow extensions, so 2.1.1 reads very much like the expected follow-up pass: less about headline features, more about making interchange and export behave properly when real projects get involved.

RealityScan 2.1.1 is now available, and while this is not the kind of release that arrives with fireworks and a new category of buzzword, it does address several parts of the workflow that tend to matter once scans actually have to leave the application and survive contact with the rest of production.

The most relevant improvements are in the COLMAP pipeline. RealityScan 2.1.1 now exports either to a flat folder structure or to the standard COLMAP directory layout, supports both binary and ASCII export, improves mask export behavior, and filters low-accuracy points automatically during export. On import, Epic has added support for the FULL_OPENCV camera model, which should make it easier to bring in a wider range of calibration data without extra cleanup elsewhere in the chain.

Mask handling is one of the more useful practical changes here. The exporter now supports AI-generated masks, and users can choose whether to keep the .mask.ext suffix when exporting into the standard COLMAP directory structure. Epic also lists fixes for cases where selected mask layers failed to export, along with corrections for quality degradation when exporting COLMAP data based on original distorted images. That is the sort of update that sounds small in a changelog and rather less small when it breaks a handoff.

Another addition is the new “RealityScan XMPs with Image List” export in the Registration exports. This makes it possible to export XMPs corresponding either to the original distorted images or to undistorted images, and to choose between the “local:1 Euclidean” and “Grid plane” coordinate systems. At the same time, Epic has removed the separate Image list export from the Alignment tab, because the same function already existed in Registration export. Exported image lists now use the .imagelist extension, which can be reused when importing inputs or input selections back into RealityScan.

There are also smaller but welcome naming and consistency changes. Texture layer names now respect the specified name, including when selecting layers for texturing. Epic also removed some extra information from those names, including 16-bit and HDR prefixes, and adjusted numbering. On the command line side, importColmap becomes loadColmap, importBundler becomes loadBundler, and importFlightLog becomes importTrajectory. Not glamorous, but coherent. That alone can save someone a mildly irritating half-hour that could be spent watching cat videos.

The fixed-issues section is long, and in this case that is probably good news. Epic lists corrections for an incorrect “model is already colorized” warning on certain LiDAR models, ignored intrinsic parameters during flight log imports, EXR import issues, misplaced imported masks, raster artifacts in depth and mask exports, black mask exports in some cases, crashes related to LOD export settings and long computations, scene transformations being incorrectly retained after COLMAP and Bundler imports, and support for importing PLY files generated by the CGAL library. There are also multiple fixes for export behavior in cameras, orthographic projections, LAS classifications, contour export, and Nira upload handling.

Epic Games documentation for RealityScan 2.1.1

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The post RealityScan 2.1.1 adds better COLMAP support and new XMP export options first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

For those who don’t know the tool: The Pixel Farm develops PFTrack, a node-based 3D camera tracking and photogrammetry system used in VFX, virtual production, and survey-driven pipelines. It exports to DCC tools including Autodesk Maya and integrates LiDAR and image based reconstruction.

The Pixel Farm has released PFTrack 26.02, a point update to its camera tracking and photogrammetry software. The release focuses on export reliability, Survey Solver behaviour and data validation rather than new solver technology. According to the published change list, the update introduces improvements to Maya export scripts, OBJ texture handling, LiDAR import logging and node connectivity within the Survey Solver. It also resolves a keyboard shortcut conflict in the Orient Camera node.

Maya export scripts corrected

The updated Maya export scripts now automatically parent background image planes to cameras on export. This addresses a long standing friction point in matchmove handoff. Previously, depending on scene configuration and export path, artists could end up manually re-parenting image planes inside Maya to maintain alignment between the solved camera and its background plate. The revised script automates this relationship at export time.

For tracking teams delivering camera solves into Maya-centric pipelines, this reduces post-export clean-up and the risk of misalignment during layout or scene assembly. The vendor statement does not detail changes to other DCC export scripts.

Survey Solver and OBJ texture loading

PFTrack 26.02 updates the way OBJ mesh textures with numbered filenames are loaded into the Survey Solver node. OBJ sequences or assets that rely on incrementally numbered texture files will now load correctly when imported into Survey Solver. The official notes do not specify naming conventions, but refer to numbered filenames in general terms.

For facilities using photogrammetry meshes or survey derived assets with multiple texture tiles, correct automatic loading reduces manual reassignment inside the node graph. It also limits the possibility of mismatched textures during camera solve refinement. The change appears limited to texture loading behaviour inside Survey Solver and does not reference modifications to the OBJ importer elsewhere in the application.

LiDAR import logging added

The update adds explicit error logging when importing corrupted or incomplete LiDAR survey data files. PFTrack supports LiDAR survey data within its camera-solving and scene-reconstruction workflows. In previous versions, incomplete or damaged files could fail during import without detailed diagnostic output.

With 26.02, the system now logs errors when such data is detected. The vendor documentation does not describe the logging format, verbosity level or where logs are written. It does state that error logging is triggered when corrupted or incomplete LiDAR files are imported.

Photogrammetry node connectivity fixed

A further fix addresses connector logic in Studio and Enterprise editions. Photogrammetry nodes can now be connected to secondary inputs of the Survey Solver where appropriate. The official wording specifies that this applies to Studio and Enterprise only.

This suggests that earlier builds restricted valid node graph connections in certain configurations, potentially limiting more complex photogrammetry driven solves. The updated connector logic restores the ability to route photogrammetry outputs into secondary Survey Solver inputs when supported by the node’s design.

The vendor has not published technical detail about which specific input sockets were affected or how the internal validation rules have changed. Not independently verified at press time.

Facilities using advanced node graphs that combine survey data, image based reconstruction and manual constraints should review existing templates to confirm expected behaviour after updating.

Scope and positioning

This release does not introduce new solver models, GPU-acceleration changes, or major UI revisions. It is positioned as a maintenance and workflow refinement update. The focus remains on export reliability, data validation and node graph correctness. For studios that rely on PFTrack for camera tracking, survey alignment and photogrammetry reconstruction, these adjustments address specific operational irritations rather than expanding feature breadth.

PFTrack is available in three editions. PFTrack Solo is priced at £699 for a permanent licence. PFTrack Studio is offered on a rental basis, with pricing listed at £59 for a five day rental period. PFTrack Enterprise pricing is available on request from The Pixel Farm. As always, facilities should confirm current licensing terms and support options directly with their vendor before procurement.

As always, new tools and updates should be tested in controlled conditions before being introduced into active production pipelines.

The post PFTrack update tidies Maya and LiDAR workflows first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

The Hochschule für Fernsehen und Film München (HFF Munich) is one of Germany’s leading film schools, offering specialised programmes in directing, production, cinematography, screenwriting, and visual effects. Infinity Hotel is a surrealist short film produced by the school’s VFX students, Vanessa Chu, Vanessa Ramovic, Jim Obmann, Emil Pogolski, Sonja Latussek, and Elena Rid, in collaboration with the departments of Screenwriting and Production. Directed by Professor Matthias Zentner, and supported by Prof. Jürgen Schopper, Prof. Sinje Gebauer and Dr. Rodolfo Anes Silveira, the project combines live-action cinematography, 3D scanning, and digital environments.

A production report by the Students

Written by Vanessa Ramovic, Jim Obmann,
Sonja Latussek, Elena Rid, Emil Pogolski and Vanessa Chu.

After completing our first animated short films as visual effects students at the University of Television and Film Munich, we selected our next joint film project. The basic idea of INFINITY HOTEL, written by students Michael Schwärzler and Jakob Smolinski, immediately suggested weaving reality and surrealism together. Themes such as inner fears and memories accompany our protagonist, Clarence, an insurance salesman travelling from hotel to hotel. He enters a strange hotel room and quickly realises that something about this Infinity Hotel cannot be right. He not only wanders through twisting corridors and distorted staircases, but also through fragments of his own memories, confronting them.

INFINITY HOTEL is a collaborative film project between the VFX students and the screenwriting and production departments at HFF Munich. Directed by Professor Matthias Zentner, the film gave us the opportunity to contribute to many parts of the production process and to realise a story that would hardly exist without visual effects.

Our experiences from the animated short films WOODLAND and LITTLE STAR, created in the first year of study, helped us build on existing knowledge while acquiring new expertise. Unlike full CGI animated short films, the main challenge this time was producing photorealistic assets and shots for a live-action film. The following article reflects on our experiences during production and outlines how the visual effects of INFINITY HOTEL were created.

Concept & Painting!

In the early stages of script development, we explored the visual identity of the mysterious Infinity Hotel. The VFX students designed the protagonist’s childhood living room, the hotel corridors and colour palettes, and created initial storyboard elements for planned VFX sequences. A concept art seminar with Luis Guggenberger encouraged us to give free rein to our imagination and broaden our creative horizons.

Paintings play a central role in the film. Early in production, we gained valuable insight into the work of the production design department through collaboration with Eva Maria Stiebler, who printed our digitally designed paintings onto canvas and brought them to life. Vanessa Ramovic, Vanessa Chu and Emil Pogolski created the paintings that Clarence observes before entering the ominous hotel room.

Each painting exists in two versions, each representing a fragmented glimpse into his memories or dreams. One version might show young Clarence playing with a toy rocket or receiving his stuffed snail from his mother. The second versions depict distorted pasts and desires, such as the boy as a real astronaut, abstracted with a snail shell instead of a head, or alone and silent in his childhood living room without his mother. The paintings act as clues to the character’s past. Four works were digitally painted in Procreate and printed on large canvases by Eva Maria Stiebler, framed in wood for the set. Two additional paintings were created as charcoal drawings on paper.

Comics!

The comic books lying on the hotel room table were illustrated by Vanessa Ramovic and depict the adventurous “Cosmic Knight” Clarence’s childhood hero and career role model. Sonja Latussek animated the Cosmic cartoon shown on the small CRT television behind Clarence using the drawing and animation software Krita. She aligned the hero’s origin story with the comic books and portrayed his journey into space. Each frame was drawn individually, giving the cartoon its distinctive two-dimensional charm. In collaboration with production design, the animation was played back on the television on set.

The Endless Spiral

From the start of pre-production, we aimed to visualise Clarence’s inner emotional state. The red spiral staircase at our second Munich location provided an ideal opportunity to depict his descent into memory. Since the physical set could not accommodate infinite depth, Vanessa and Jim digitally extended the staircase. They captured a 360-degree FARO LiDAR scan of the stairwell, converting the spatial data into a 3D environment.

It was striking to see how precisely the point clouds generated by Faro Scene replicated the physical world. The resulting model was adjusted and extracted in Blender, where Vanessa and Jim animated the structure. The deformation of the staircase was particularly complex and was achieved using a geometry node system in Blender. Vanessa recreated the staircase texture in Substance Painter, based on reference photos taken on location by the entire VFX team.

The final compositing step involved integrating the digital staircase into the original footage. With guidance from lecturer Martin Tallosy, Vanessa learned how to use rotoscoping in Nuke to create nearly invisible transitions between plate and CG elements. Martin supported the integration of CG footage into all VFX shots and helped with initial colour adjustments. Lecturer Ando Avila taught us to track handheld camera movement using 3D Equalizer, enabling Vanessa and Jim to transfer the motion to the digital 3D model. Working closely with our instructors allowed us to explore new tools and combine traditional sets with digital visual effects.

The particular challenge with the spiral staircase was that the real staircase on set did not have a perfect circular shape. This required us to develop a believable transition from the set staircase into our circular CG spiral staircase that extends into depth. It was also meant to feel less steep and cramped than the real-world reference. Another challenge lay in the angles of the steps. On the real staircase, the steps were not perpendicular to the circle’s tangent at their respective positions, but instead met the circular form at a slightly offset angle. For the set extension, however, we wanted an aesthetic solution that would integrate more harmoniously into the staircase. Our goal was therefore to build a transition in which the skewed angles of the set staircase would gradually evolve into the perfect roundness of the digital staircase. We opted for a smooth progression: the closer one gets to the real staircase, the more angled the steps become, while further down they eventually align perfectly perpendicular to the respective circle tangent. This created a flowing transition between the physical and the digital staircase.

Vanessa Chu found it particularly challenging to implement the staircase in perspective in a way that felt believable while simultaneously conveying an endless depth. Normally, depth is not perceived very clearly in spiral staircases. However, in order to tell the story that this staircase extends infinitely, we had to work with tilted CG spiral staircases. Vanessa Chu and Jim Obmann therefore searched for a method to display the 3D model at an angle and stretch it in depth without introducing errors in the geometry.

By the time the iterations and feedback from Jürgen and Matthias were incorporated, the basic animation workflow had already been established. The professors’ feedback therefore focused primarily on lighting conditions and the intensity of the animation. Jim developed a workaround using a geometry node system and found a solution that allowed the staircase to be stretched in depth. Physically, this staircase is not correct, but for our visual storytelling this approach worked very well. At this point, physics was deliberately bent a little in order to convey the desired impression of infinite depth.

An Elevator Ride into the Psyche

The elevator was symbolically conceived in the script as a vehicle transporting Clarence through different layers of memory. In winter 2024, Emil previsualised the first elevator scenes, experimenting with lighting and composition to send the elevator into a threatening depth populated by oversized snails.

After Vanessa developed the elevator design through multiple concept drawings, collaboration with production designer Eva Maria Stiebler became essential. While the elevator appeared as a 3D object in full CG shots, it was also built physically in the HFF film studio. Digital concepts and real-world patination informed each other, as Vanessa’s designs guided the construction, which in turn defined the dimensions for Emil’s 3D model.

Sonja Latussek supported the team with detailed textures, giving the elevator a realistic appearance. She also carefully textured small debris objects placed on the elevator roof. Once models were finalised, Emil and Vanessa developed the layout for three full CG shots, stacking snail shells in front of a dark background. Elevator chain swings and dangerous pendulum movements were animated by Vanessa. In consultation with director Matthias Zentner and Professor Jürgen Schopper, Emil built the lighting setup, handled compositing, and fine-tuned lighting digitally.

A central task was the transfer of Vanessa Ramovic’s concept drawings into a precise 3D model. A key aspect of this work was creating a coherent connection between the set construction and the digital elevator. To ensure this, particular attention was paid to a dimensionally accurate approach. In retrospect, Emil Pogolski and Vanessa Ramovic would primarily invest more time in texturing and look development. They would also carry out tests under the actual lighting conditions of the shots at an earlier stage, in order to better align materiality and mood.

To integrate the realistic elevator into the surreal environment, Jim inserted real footage of the actors inside the physical elevator into the digital model opening. Emil added digital dust particles to intensify the ominous abyss and blend live-action and CGI seamlessly.

The Distoring Corridor

Another highlight was the hotel corridor that begins to warp and distort. After Vanessa Chu and Elena Rid created initial concepts, Jim modelled the corridor based on a long basement room at the location, captured via FARO LiDAR scanning and photogrammetry. Since the corridor needed to deform dynamically, Jim tested various geometry node systems to allow distortion at arbitrary points.

Simulating an infinite corridor directly would overwhelm most computers, so Jim devised a trick by scaling the corridor into depth. Viewed through Blender’s camera, the corridor appears endless. He developed a setup allowing control over both roll axis and depth movement. This resulted in a 50-metre corridor segment that, when scaled, created the illusion of infinity. Within this segment, movement allowed the corridor to emerge and disappear into depth.

Each light element within the segment could be controlled individually, enabling transitions from white light to threatening red flames that visually pursued Clarence. It was essential to integrate these light sources with the original plate.

Lighting movement on set had to be transferred to the 3D world and synchronised with the treadmill speed on which the protagonist ran. Once physical conditions were translated into Blender, the composite could function correctly. Jim also handled greenscreen keying and camera tracking, removing the original background and inserting Clarence into the rendered 3D corridor.

The Snail and why it should be feared

The gigantic snail shell threatening to pull Clarence into his dark past was a central element of the film. Elena Rid began sketching snail concepts before the story was fully defined. Inspired by horror films such as I Saw the TV Glow, the snail was designed to feel out of place, like a relic from another world. It represented a mutated version of Clarence’s childhood plush snail, distorted by grief.

At the beginning, a more classic texture was planned for the snail. As the planning progressed, however, the idea emerged to give it a subtle resemblance to a skull. Elena Rid then stretched the 3D model of the snail so that the spiral at its center would recall the hairstyle of Clarence’s mother. During sculpting, the student worked in fine cracks. Elena mainly used the cloth brush to add further small, swirling details and folds to the surface. Small indentations and a pore-covered structure were also incorporated into the sculpt. Elena primarily based this work on the previously created concept art and additional reference photos of old bones.

To achieve the prehistoric, fossil-like look, Elena engaged intensively with the main character. The snail thus served as a symbol for a very old, deeply buried trauma of Clarence. As references, the student mainly used an ammonite fossil from a museum.

Elena later modelled and textured the snail during the VFX phase. It was not intended as a static prop, but as a manifestation of Clarence’s fears and inner conflict, visually referencing the stuffed snail in his hand. Elena sculpted the primary snail in Blender. Additional snails with varied surfaces and shapes were created with Vanessa Chu. Texturing in Substance Painter, supported by lecturer Birgit Hämmerle, resulted in a photorealistic surface with a fossilised yet “moist” quality.

Elena adjusted lighting intensity and temperature, rendered the snail shell, tracked scenes with Ando Avila in 3D Equalizer, and refined them in a complex Nuke setup.

In several iterations, the exact shape of the “eye” was defined: how strongly it should protrude, in which direction the folds should run, and how the desired effect could best be achieved. In addition to a fold that functioned like the snail’s eye, the inner hole of the snail was also intended to resemble a screaming mouth in a face. In this area, Elena Rid and Jim Obmann worked together on the interior of the snail. Jim created a soft mask in Blender that fades toward the edge of the hole. External light sources were not supposed to influence the interior. In the end, it was meant to appear like a black hole that almost sucks Clarence in.

Texturing in Substance Painter was Elena Rid’s first experience with the software, which initially made it a challenge. We wanted to achieve a moldy look, which the student built up using many layers of moss brushes in different whitish and greenish tones on the base texture. Most of the fine grooves in the snail texture were therefore created in Substance Painter, as the details would otherwise have become too small during modeling. The focus was placed more strongly on a bony, fossilized surface.

Since no greenscreen was used, Martin Tallosy assisted with rotoscoping. Colours, contrasts, and brightness were adjusted to integrate the snail seamlessly into live-action footage. Vanessa Chu, Vanessa Ramovic, and Sonja Latussek assisted with camera tracking. Accurate match moves were essential for positioning the digital camera correctly within the large hall.

Learnigns from Set Supervision

After working on animated films in the first year, we eagerly anticipated shooting on a real film set. Preparation involved understanding the responsibilities of VFX supervision on set, ensuring VFX shots were filmed and documented correctly to avoid post-production issues. Asynchronous supervision courses at CAVE Academy helped us learn LiDAR scanning, photogrammetry, and reference photography.

Once preparations and pre-produced props were complete, the four-day shoot began. Supervisory duties rotated among the team, giving everyone insight into all aspects of the role. Tasks included logging VFX shots, recording focal lengths and camera data, capturing shadows using grey balls, and placing tracking points on greenscreens. Colour checkers ensured colour accuracy and white balance. Two shoot days took place at the Munich location for corridors and reception scenes. The remaining days were spent at the HFF film studio for elevator and living room scenes.

Mentor Jan Stolz provided invaluable support as set supervisor. Cinematographer Torsten Lippstock shot the film on an ARRI Alexa 35. Simon Burger introduced us to the role of the Digital Imaging Technician. Mihail Dervenski guided data management and later edited the film, aligning technical expertise with the director’s vision.

Sound Mixing and Grading

Creating a dark atmosphere was essential. Composer Lukas Stipar, previously involved in WOODLAND, delivered a soundtrack that added weight and intensified tension. Dr. Rodolfo Anes Silveira supervised post-production sound, enhancing clarity and authenticity. A Dolby Atmos mix was created at PHAROS Studio 1, where Tschangis Charokh demonstrated object-based audio placement. Andreas Lautil handled colour grading, giving the film a consistent dark-warm palette.

Conclusion

In retrospect, INFINITY HOTEL was an exciting project for us, from which we drew important personal and professional insights.

For Sonja Latussek, it became clear above all that it is important to define clear areas of responsibility at an early stage. In hindsight, she feels she should have paid closer attention from the outset to the fixed tasks that remained under her responsibility and were primarily related to the film’s visual look, such as the textures of the snail or the elevator. An unexpected challenge for her was greenscreen compositing in Nuke, which proved significantly more complex in some scenes than initially anticipated. Camera tracking, on the other hand, went very well. Sonja learned how tracking works in principle, which points in space are suitable for tracking, when they do not work, and at what point a track becomes truly precise. Although she found all areas of on-set production particularly exciting, she would like to focus more strongly on 2D work in the future. She found the 2D animation of COSMIC KNIGHT very pleasant, as it integrated coherently with the CRT television.

Vanessa Chu mainly emphasises the importance of critically questioning technical statements and not blindly relying on hypothetical possibilities. It became apparent that an ISO setting that was too high on the Alexa camera led to heavy image noise, which meant that tracking points in 3D Equalizer had to be painstakingly corrected by hand. She therefore advocates handling technical parameters such as ISO more sensitively in the future. She also emphasizes the importance of collecting as much data as possible on set and communicating early to the production that time must be scheduled between VFX shots to gather data such as references, measurements, and scans.

Emil Pogolski summarizes his conclusion with a simple but fitting guiding principle: “Make it good, kid.” From his perspective, the production of INFINITY HOTEL proceeded overall without major complications. Planned ideas could be implemented, and post-production was structured, even if it took longer than originally planned.

For Elena Rid, it became particularly clear in retrospect how valuable an even longer and freer concept phase would have been. Elena would have liked to work with more concepts and, above all, to experiment more with the snail. Due to time constraints, this was only possible to a limited extent within the project scope. For future work, the student wants to consciously allow more room for experimentation. At the same time, Elena looks back very positively on the rest of the production process. The team made it through the intensive phase well, and in her view, the scheduling in particular proved to be a major strength of the project.

Vanessa Ramovic believes that most aspects of the production worked very well. Towards the end, she and Emil invested a great deal of time in post-production because the elevator compositing iterations required significant effort. She would also like to develop more concepts in the future and test different lighting moods more intensively. Her personal conclusion is less about technology and more about personal attitude: not losing the joy of the work. For her, making films means expressing something and perhaps even putting a smile on someone’s face. This inner light should not be allowed to fade.

Acknowledgements

What was special about our second year of studies at the University of Television and Film Munich was that our entire cohort worked together on a single project. Without question, this was a true team effort in which all six students contributed their existing knowledge to the film while continuing to develop their skills.

Our special thanks go to our professor Jürgen Schopper, who provided us with strong support in VFX supervision. His vision and creative input helped us, during the weekly classes known as “weeklies”, to push the VFX shots to their final form. Prof. Sinje Gebauer, Dr. Rodolfo Anes Silveira, Berter Orpak, Jonas Kluger, Martin Tallosy and Petra Hereth, who together with Professor Schopper form the chair of the VFX degree programme, supported us throughout the entire year with their expertise across various areas of the VFX pipeline.

Together with Prof. Sinje Gebauer, we ensured that all assets and shots were realised and integrated into the overall flow. INFINITY HOTEL introduced us to working with new VFX tools and to closer collaboration with the screenwriting and production departments at the university. Our screenwriters Michael Schwärzler and Jakob Smolinski inspired us early on with precise story ideas, which we were already able to incorporate creatively into our concept drawings in November 2024. Nevertheless, the further development of the material was a collective exchange, in which we, along with our director and professor Matthias Zentner, contributed ideas and gained insight into the authors’ working processes.

Our producers Sonja Hopf and Konstantin Holzner supported us from the very beginning and guided the production with their extensive expertise. While we, as VFX students, largely operated like a small VFX studio during post-production, we were involved in the film from the outset and gained deep insights into various departments, such as production design and casting.

We would also like to thank our actors Till Raskopf, Jonathan Tittel, Nick Woodland, and Sophie Melbinger, as well as the entire film team, for bringing the fictional characters to life and for creating a strong short film together. After the successful completion of the hotel, we were finally able to present the film to a broad audience and guests from the VFX industry at our premiere as part of the VFX Reels 2025 on 27 November 2025 at the HFF. The film premiered at the VFX-Reels 2025 on 27 November 2025 at HFF Munich.

The Producers’ view

WRITTEN BY SONJA HOPF AND KONSTANTIN HOLZNER

As student producers, our task was to realise a live-action narrative film with a high proportion of visual effects, from development through to festival distribution. Working closely with the VFX and screenwriting students, we entered an entirely new production terrain. One of our key learnings was the necessity of considering VFX shots and technical requirements from the very beginning.

We developed a solid understanding of how previs is created and how it functions, as well as what is required on the production side to make a set truly “VFX-ready”. This included scheduling time buffers for tracking markers and scans and actively coordinating between creative departments and the VFX supervisor. It became clear early on that every shot requires detailed, early planning. Learning to realistically assess how many shots can be achieved in a shooting day, and how VFX-heavy shoot days must be calculated and structured, proved to be a particularly valuable challenge.

The project could only succeed as a collective effort. Coming together early in development allowed us to contribute as creative producers and gain a deeper understanding of both the material and the production challenges. Continuous communication across departments was essential, especially as locations changed, the set expanded, and creative ambitions had to be balanced against available resources. Working with professional heads of department set a high bar and challenged us to meet professional standards, a goal we ultimately achieved, resulting in work we are proud of.

The post Infinity Hotel: Endless Rooms, Endless Renders first appeared on DIGITAL PRODUCTION and was written by HFF Hochschule für Fernsehen und Film München.

For those who don’t know the tool: Kiri Engine is a photogrammetry app for iOS, Android, and web, built by Kiri Innovations. It processes 3D captures into textured meshes, often used in VFX, games, and AR. The firm now adds produce to its growing scan library.

A produce aisle for 3D artists

Kiri Innovations has released a new asset collection featuring over 140 3D-scanned fruits and vegetables. The pack contains 141 individual models captured using photogrammetry, sourced from users of the Kiri Engine mobile and web app. The assets include both common produce such as apples, bananas, and tomatoes, and less typical items such as mangosteens, lychees, and dragonfruit. Each model comes with production-ready geometry that has been retopologised and UV unwrapped. The data is supplied in both FBX and native Blender formats, making the pack directly usable across most 3D content creation tools.

Properly textured and LOD-ready

Every scan includes PBR (physically based rendering) texture sets with colour, normal, ambient occlusion, roughness, and height maps. Texture resolutions reach up to 4K, and the files are provided in JPEG, PNG, and EXR formats for compatibility across different render pipelines. Three levels of detail (LOD) are provided per model, simplifying the use of these assets in realtime engines such as Unreal Engine or Unity. No additional setup appears to be required.

Commercial use without restriction

All 141 assets are distributed under a CC0 licence. This places them in the public domain, allowing full commercial use with no attribution or licensing restrictions. Downloads are available via the Kiri Engine Web platform. A free user account is required to access the pack.

Production reality check

While the scans appear clean and the assets are retopologised, Kiri does not specify polygon counts or per-asset texture resolutions. Artists should test the files in their preferred DCCs before using them in a live production pipeline. File size and compatibility can vary across applications. This release continues Kiri’s ongoing effort to promote user-generated 3D scan sharing and expand its public library. The company positions these assets as examples of the quality achievable with its mobile scanning technology. New tools and content packs like these should always be tested in production environments before use to confirm performance, scale accuracy, and shading consistency.

The post Free 3D Fruit: Fresh Assets, No Pesticides first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

For those who don’t know the tool: PFTrack is The Pixel Farm’s flagship 3D camera tracking and matchmoving software, used in VFX and virtual production pipelines for precise camera solves, photogrammetry, and scene reconstruction. It works alongside PFClean and integrates with DCCs from Maya to Nuke.

Lens distortion overhaul

The 25.11.13 release introduces new anamorphic and non-linear distortion models, smarter grid detection, and automatic selection of the most suitable lens model for each shot. The Lens Management system also now allows exporting distortion data directly into supported host applications.

Tracking tools refined

Both Auto Track and User Track nodes gain expanded editing controls in the Cinema workspace, including track grouping and motion prediction. The Localised Motion Prediction algorithm enhances feature consistency on fast-moving footage. Camera and Survey Solver nodes receive improved parameter control and faster iteration feedback.

Photogrammetry and modelling upgrades

The Photo Mesh node’s performance and memory management have been re-engineered to allow significantly larger mesh builds, particularly on macOS. Image Modelling introduces user-defined primitives, enabling custom reference geometry during scene reconstruction.

Sensor databases and third-party data

With the 25.12.19 build, PFTrack adds support for external camera sensor databases, beginning with integration of Matchmove Machine’s CamDB. This allows accurate sensor metadata import to improve focal calibration.

Node and UI polish

Across all 2025 releases, many nodes—including Geometry, Solver, and Point Cloud—benefit from small but meaningful updates: faster point cloud generation, improved solver convergence, and clearer error feedback. The general UI receives smoother interaction within Cinema viewports and enhanced undo stability.

Quality-of-life improvements

The 25.10 update improved bundle adjustment speed and tracking robustness on heavy footage. Version 25.09 refined Python scripting APIs, expanding access to internal data for pipeline automation. Collectively, these tweaks make PFTrack less prone to small but annoying interruptions mid-solve.

Licensing reshaped

After user demand, The Pixel Farm has reintroduced perpetual licences alongside subscription and floating models. Solo, Studio, and Enterprise editions remain available, with perpetuals offered for PFTrack only. Pricing is listed on The Pixel Farm’s store.

Tested before trusted

The Pixel Farm recommends reviewing node behaviour in controlled test scenes before deploying 2025 builds into live productions. As always, newer algorithms can subtly alter solver results between versions.

// https://pftrack.thepixelfarm.co.uk/documentation/changelog.html

The post PFTrack 2025: Matchmoving gets its groove back first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

For those who don’t know the tool: Kiri Engine is a photogrammetry app that turns real-world captures into 3D models, targeting artists in VFX, games, and visualisation. Its ecosystem now extends into Blender with a set of free add-ons designed for environment work. Mesh Wrap is the latest entry in this toolkit, joining other utility plug-ins for scan preparation and scene layout.

A Free Add-on for Wrapping 3D Terrain Scans

Kiri Engine has released Mesh Wrap, a free add-on for Blender designed to simplify how artists integrate terrain scans into base meshes. Unlike Blender’s default shrinkwrap modifier, Mesh Wrap is built specifically for photogrammetry-based environments. It projects surface-scanned meshes, such as rock faces or terrain tiles, onto clean base geometry while preserving scan detail and alignment.

The add-on supports Blender 4.5 and newer and is available for free download via a Kiri Engine account. It is intended for terrain and surface data, not for closed or solid meshes.

Two Workflows: Planar and Scatter

Mesh Wrap provides two distinct workflows. Planar Wrap handles the projection of a single mesh onto a base surface. Scatter Wrap distributes and wraps multiple scan meshes across a terrain, enabling fast environment coverage without manual placement. Both tools rely on a ray-casting projection system, with direction controls for world or object axes. A visible gizmo helps users verify projection direction and adjust wrapping behaviour. Misaligned objects trigger a “surface not found” warning, an indicator of an incorrect projection axis or displaced origin.

Mesh Preparation Tools

Before wrapping, the add-on offers mesh-preparation utilities to correct rotation, fix skewed origins, and align object pivots. The Auto Rotate feature attempts planar alignment, while origin controls allow setting to the lowest, highest, or median point of the mesh. These adjustments directly influence how accurately the scan conforms to the target surface.

Precision Controls and Cleanup

Mesh Wrap introduces displacement-strength adjustments, overlap handling, and boundary-snap features. These tools refine how the wrapped scan adheres to the base terrain and resolve clipping or intersecting faces. The Overlap Cleanup menu includes modes to remove or smooth intersecting faces and distance-based masking to recover deleted geometry. The Snap Boundary to Surface option ensures that edge vertices align seamlessly with the target mesh, creating clean joins between tiles or blended terrain segments.

Scatter Workflows and Performance

For larger environments, the Scatter Wrap workflow distributes multiple terrain scans across a defined surface. Users can select a single mesh or a collection and enable automatic Decimate modifiers to lower polygon counts. Scatter methods include Grid (planar distribution) and Normal-Aligned (surface-conforming), both offering controls for density, scale, and scatter seed randomisation.

Performance optimisation is a recurring theme. Kiri advises scattering only within the camera’s field of view and applying modifiers once layouts are final. Since all scattered instances are “realised” geometry, high-poly scenes can quickly affect viewport responsiveness. Applying and cleaning geometry after wrapping is recommended.

Practical Notes

The add-on’s defaults are tuned for planar, Z-axis-oriented wrapping. Artists can switch projection axes for vertical surfaces, such as cliffs or walls. Decimation ratios are adjustable per object, and modifiers can be baked for performance. A small “tick” icon applies modifiers directly from the panel.

Availability and Requirements

Mesh Wrap is free for all Blender users with a Kiri Engine account. It installs through Blender’s standard add-on interface. Documentation and video guides are available on Kiri Engine’s YouTube channel. As with any new production tool, artists should evaluate stability and compatibility before deploying it in critical pipelines.

The post Terrain Wrapping Made Easy: Kiri Engine’s Free Blender Add-on first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

New Folder Rules: Asset Directory System

ZBrush 2026.1 introduces a centralised Asset Directory System on desktop. All user data including custom UIs, hotkeys, brushes, materials, plugins and Lightbox assets now lives outside the installation path.

Each user can assign or change the folder location in Preferences → Asset Directory. Three functions are available: Open Directory, Change Location, and Reset to Default. A restart is required after changing the directory, triggering automatic generation of a clean folder structure. This design supports environments where multiple users share the same ZBrush installation, such as classrooms or studio workstations. It also allows artists to maintain separate configuration sets for different projects or clients by switching between asset directories. Plugin loading has been restructured, user installed plugins load after Maxon’s native plugins and appear under ZPlugin, beneath ZColor, clearly separating custom tools from built ins.

IMM Foldering: Order in the Chaos

Insert Multi Mesh (IMM) brushes can now contain internal folder hierarchies. A large IMM brush can be subdivided into named groups such as Cylinders, Capsules, Clothing, or Accessories, visible in the brush’s M popup menu. To build a foldered IMM, users organise SubTools into SubTool folders, then execute Brush → Create Insert MultiMesh. ZBrush automatically generates IMM folders corresponding to the SubTool folders. This process no longer requires external plugins. Foldered IMMs are especially useful for large production brush libraries, where hundreds of mesh variations were previously stored as flat lists.

Retopo Brush: A Dedicated Topology System

ZBrush 2026.1’s headline feature is the new Retopo Brush, available on both desktop and iPad. It introduces a topology specific mesh type that snaps across all visible SubTools and supports symmetry, full vertex, edge, and polygon editing, and iterative rebuilds.

Core interactions:
Tapping places points. Holding Spacebar previews polygon fill and adjusts draw size. Pressing and holding Alt on an edge extrudes geometry, releasing Alt switches between quads and triangles. Holding Alt on a face deletes a polygon. Control dragging in empty space removes unused points. Control while extruding sets segment counts. Spacebar + drag on an edge adds loops. Alt + drag draws temporary guide lines, drawing two lines in sequence auto fills the space between them with a quad strip.

The brush uses a two size system, a normal Draw Size for editing and a secondary Spacebar Draw Size for temporary polygon previews. In Brush → Retopology, key parameters include Snap Threshold, Move by Brush Size, Smooth Border Behaviour, Adaptive Draw Size and Edge Flow Drawing.

A Smooth Retopo mode is included. It automatically conforms to underlying geometry across all visible SubTools, maintaining surface continuity during smoothing. Holding or releasing Alt determines whether boundary vertices remain fixed or move. Existing meshes can be converted into retopo meshes by tapping them and selecting Convert Mesh instead of Create New. This allows refinement of ZRemesher results or cleanup of extracted geometry without restarting topology work.

Patch System: Templates for Rapid Topology

The Retopo Brush now includes a Patch System accessible via its IMM folders. The set contains predefined square, circular, and multi resolution patch templates.

To use patches, place a single point, hold Alt and drag to draw a patch, then tap to confirm. The patch automatically snaps to the surface. Additional loops can be inserted and smoothed after placement.

Each patch can switch to Lattice Mode by tapping Alt on its preview gizmo. This mode adds a deformation cage for adjusting form before confirming the patch. Lattice controls are non symmetrical by design, but patches themselves respect symmetry on placement.

ZModeler Integration: Old Meets New

Retopo meshes remain fully compatible with ZModeler, allowing direct access to ZBrush’s polygon editing operations. Supported functions include Slice Mesh (multi cut), Inset, Weld, Bridge, and loop deletion. ZModeler’s Slice tool is particularly relevant for defining seams or redirecting topology flow before final projection. Because Retopo meshes use native topology structures, they can be refined or combined with existing ZModeler workflows without conversion.

Photogrammetry on iPad: Capture and Sculpt

ZBrush for iPad now supports photogrammetry capture using the device’s LiDAR sensor and camera data. The workflow begins from a new Capture mode on startup. Users frame an object within an on screen bounding box, then perform multiple passes, typically 40 to 100 photos for best results.

ZBrush generates a dense point cloud and a textured mesh with automatic UVs. The resulting asset includes both geometry and colour data.

A suggested post processing pipeline includes converting the texture to an alpha map (Texture → Make Alpha), extracting displacement detail to a subdivided mesh, cleaning geometry via Dynamesh, and re projecting fine detail through Project History or Extractor. Artists can then unwrap with UV Master and transfer PolyPaint data back to texture. The feature is primarily intended for matte, non reflective subjects such as props, rocks, sculptures, shoes, or vehicle parts.

Quick Search: iPad Only Navigation Aid

A new Quick Search system, currently exclusive to iPad, provides a global search interface for palettes, buttons, sliders, brushes, and actions. Keyboard users can navigate results using arrow keys and adjust slider values directly within the search window. Search history is preserved between sessions. This tool can accelerate demonstration setups and help new users locate hidden interface elements without scanning menus manually. The feature is not yet present on the desktop version.

Compatibility and Feature Parity

Both the desktop and iPad editions now share the Retopo Brush and Patch system, providing near identical topology workflows across platforms. IMM folders also behave consistently in both environments. The new search system remains iPad only for now. The previously previewed UV Editor and desktop UI overhaul, shown at the ZBrush Summit, are not part of version 2026.1. Likewise, a Substance Painter bridge is mentioned in roadmap discussions but not included in this release. All features described are part of the verified 2026.1 release build at the time of publication.

Production Reminder

As with any structural update, particularly those affecting topology, file management, and plugin loading, teams should verify stability and compatibility with existing pipelines before deployment in production. Testing should include multi user directory switching, plugin load order, and mesh conversion integrity under the Retopo Brush.

Production Supplement: Pipeline Implications and Testing Advice

In production, the new Asset Directory System should be integrated carefully with version control and profile management. Studios maintaining multiple artists per workstation can now define consistent folder hierarchies on network volumes without touching program directories. For automated deployments, the Change Location option can be configured through startup scripts, although a restart is mandatory. This behaviour simplifies backup and restores but requires new onboarding procedures for workstation images and classroom templates.

For topology artists, the Retopo Brush replaces the need for third party retopology plugins or external hand topology tools. However, it introduces a new data structure that behaves differently from traditional subtools. Retopo meshes do not respond to deformation or subdivision until converted, and certain sculpting features remain unavailable until confirmation. Pipeline TDs should test retopo mesh export behaviour with Alembic and FBX before committing the workflow. The photogrammetry pipeline on iPad is promising, but the mesh density and UV precision require evaluation before using scans for high end texturing or displacement capture.

The post ZBrush 2026.1: Retopo & Assets first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

Epic Games has released version 2.1 of its desktop 3D-scanning software RealityScan. The update introduces expanded LiDAR workflows, automation interfaces for production pipelines, and several image-processing and export improvements.

LiDAR, SLAM and classified point clouds

RealityScan 2.1 now supports importing SLAM (Simultaneous Localisation and Mapping) data, including trajectories, images and point clouds from drones or handheld scanners. SLAM captures can be merged with standard photogrammetry or laser scans, improving reconstructions in large or complex environments. The release adds support for classified point clouds in LAS/LAZ formats using ASPRS classification tags. Users can include or exclude specific classes, such as vegetation or vehicles, when generating meshes, a workflow particularly useful for urban or environmental captures. These additions extend RealityScan beyond photogrammetry into hybrid LiDAR and image-based scanning.

Automation and server integration

Version 2.1 places strong emphasis on automation. A new command-line interface (CLI) provides batch commands for import, reconstruction, and export tasks. It replaces the older reporting system with a template-based data extraction tool that can generate structured outputs for tracking and review. RealityScan can now be remotely controlled through REST and gRPC APIs, allowing studios to run automated or farm-based scanning operations. Sample Python scripts are included to demonstrate integration. For headless setups, a Linux-compatible CLI build is provided. It operates through a bundled Wine environment and can process alignments, meshing, texturing and exports without a GUI, supporting scalable production farms.

Workflow and quality improvements

UV unwrapping has been revised with a coloured checker map that visualises distortion, adjusted thresholds for large-triangle removal, and a default-enabled texture defragmentation chart to maintain clean UV layouts. Rendering now includes a “render-camera view” that reuses the original capture camera positions. Artists can match or remove lens distortion and export surface normals in world or camera space. Export formats have been expanded with OpenCV registration files, XMP metadata for distorted and undistorted imagery, and improved COLMAP export that retains native distortion parameters.

Licensing, hardware and availability

RealityScan remains free for individuals or studios earning under US $1 million per year. A commercial licence costs US $1,250 annually. The software supports Windows 8 and later or Windows Server 2008 +. A Linux CLI build targets Ubuntu 24.04 and Fedora 39 via Wine. Because RealityScan’s reconstruction relies on CUDA acceleration, an NVIDIA GPU is required.

RealityScan Mobile 1.8

In parallel, Epic Games released RealityScan Mobile 1.8 for iOS and Android. The update adds AR-guided capture, object-mode background removal, focus peaking, mesh clean-up tools, a capture-interval timer, and an optional watertight mesh export for 3D printing. It remains free and targets rapid on-site asset capture for integration into RealityScan desktop or Unreal Engine pipelines.

RealityScan Mobile 1.8 with Tools for On-the-Go Scanning

Conclusion

RealityScan 2.1 advances Epic’s scanning suite into a hybrid LiDAR and photogrammetry toolset, pairing automation with precision UV and export control. The update strengthens its role as a practical choice for VFX, game, and visualisation workflows. As always, test stability and compatibility before deploying the new release in production.

The post Epic Games updates RealityScan: 2.1 out first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

The mobile version of the photogrammetry app RealityScan Mobile 1.8 by Epic Games has been updated to version 1.8 for both iOS and Android. The official release notes detail several new features, fixes and known issues.

What’s new: Capture modes and tools

RealityScan 1.8 introduces three shooting modes designed for different use cases. AR Guidance mode employs augmented reality overlays to display a live point-cloud and photo positions, showing where more images are needed for complete coverage. Object Mode adds advanced camera controls and automatic background removal, allowing users to rotate or move the object for a full capture. Standard Mode offers the same controls without background removal, suitable for scanning objects within their original environment.

A new interactive view cube enables rotation from any angle and switching to predefined orthographic views. Mesh Clean Up tools now allow users to select and delete unwanted parts of a generated mesh using lasso or rectangle selection. The addition of focus peaking overlays highlights areas that are sharply focused, improving capture quality in-camera.

Version 1.8 also introduces a capture interval timer, enabling automatic photo capture at regular intervals — a practical addition for turntable or tripod setups. The new watertight mesh option allows users to choose between generating sealed, 3D-printable meshes or non-watertight ones that may preserve more surface detail when masking has not been used. Continuous light mode gives control over the phone’s flashlight, allowing it to remain steadily on for low-light environments instead of flashing intermittently.

Practical relevance for production users

For professionals in postproduction, VFX, realtime graphics, or game development, the new features significantly improve mobile photogrammetry workflows. AR Guidance reduces coverage errors by providing live feedback during scanning. Object Mode’s background removal results in cleaner object isolation, an advantage when creating assets for VFX or realtime engines. Focus peaking and the interval timer support more consistent capture, particularly for stationary or rotating subjects.

The option to choose between watertight and non-watertight mesh output provides flexibility depending on end use, whether for 3D printing or game-ready asset creation. On-device mesh clean-up tools reduce early cleanup effort before exporting to desktop software. Overall, the update moves RealityScan closer to a professional capture companion for on-site or field asset collection.

Fixes, known issues and considerations

RealityScan 1.8 resolves several bugs across both iOS and Android platforms. On Android, it fixes poor image quality and large HEIF file sizes when scanning in AR mode, as well as issues with photo orientation on certain devices such as the ASUS ROG 6D Ultimate. On iOS, the update corrects missing flash indicators, projects stuck in “Processing” status, user sign-outs during scanning, and problems with sharing scans to Sketchfab when minimising the app.

Several issues remain unresolved. On Android, reprocessed models may appear cropped. On iOS, newly processed projects can still get stuck in “Processing”, the top-to-back view transition remains unsmooth, and differences persist between RAW and JPEG image outputs. Clean installs can sometimes result in a black camera view until the app is restarted.

Before deploying this release in any professional environment, users are advised to test performance and output on their specific devices and within their pipeline to confirm reliability and image consistency.

The post RealityScan Mobile 1.8 with Tools for On-the-Go Scanning first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

KIRI Innovations has shipped KIRI Engine 4.0, a major update to its mobile 3D scanning app for Android and iOS. The release focuses on faster photogrammetry, higher capture limits, AI-based texture generation, and new freedoms for Basic users.

Faster photogrammetry, cleaner meshes

Photo Scan mode now processes data in about two minutes per scan, compared to nearly ten in earlier versions. The update also improves handling of low-texture surfaces, producing more stable reconstructions with fewer artefacts.

Augmented reality for capture coverage

A new AR mode projects captured camera positions into 3D space, allowing users to spot gaps in coverage and reshoot missing angles. This aims to reduce reconstruction errors caused by incomplete data.

Raised photo upload limits

The app now supports larger capture sets. Basic users can upload up to 150 photos per scan (up from 100), while Pro subscribers can use up to 500 photos (previously 300). This should improve detail and accuracy in complex object scans.

Unlimited exports for everyone

The former cap of three exports per week for Basic accounts has been removed. All users can now export an unlimited number of scans in standard formats including OBJ, FBX, STL, GLB, glTF, USDZ, PLY, and XYZ. This change affects both photogrammetry and LiDAR workflows.

AI-powered PBR material capture

Version 4.0 introduces an AI-driven physically based rendering (PBR) algorithm, built on a diffusion model. According to KIRI Innovations, this generates more realistic and consistent material textures directly from scanned data, reducing the need for manual texturing.

On-device full-resolution previews

The app now supports full-resolution model previews on mobile devices, enabled by a new compression method. Users can toggle textures on and off to inspect raw geometry, addressing a long-standing limitation of mobile-based workflows.

Pricing and availability

KIRI Engine remains free to download. Pro accounts cost US $17.99/month or US $79.99/year, unlocking higher photo limits and features such as 3D Gaussian Splatting (3DGS). Version 4.0 is available now for Android 7.0+ and iOS/iPadOS 15.0+ devices.

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Final Note

The new release removes significant bottlenecks in KIRI Engine’s free tier while introducing AI-driven texture tools for Pro users. As always, readers should verify output quality and workflow compatibility in test projects before adopting the tool for production.

The post Faster, wider, cleaner: KIRI Engine 4.0 drops mobile scan limits first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

Meshroom 2025.1 brings pipeline templates (ready-to-use node graphs), a new plugin system with script editor and Meshroom Hub, segmentation nodes for targeted reconstructions, Reflectance Transformation Imaging and Multiview Photometric Stereo, experimental Lidar and point cloud support, Blender preview via ScenePreview, survey point injection from 3D Equalizer, and multiple UI and graph editor improvements.

Templates instead of tinkering

The new Meshroom 2025.1 release introduces pipeline templates. Users can start projects with one of 24 predefined node graphs, open existing setups, or build from scratch. Templates can be saved, exported and imported, making them suitable for studio pipelines and collaborative work.

A more open Meshroom

Under the hood, Meshroom has been decoupled from AliceVision, making it more modular. The application still ships with AliceVision, but the restructuring allows for easier integration of external code, AI and ML models. The new plugin system enables developers to add custom nodes. A script editor is now part of the interface.

The Meshroom Hub already offers plugins for Gaussian splatting, monocular depth estimation, optical flow and more. Currently, testing plugins requires some development skills to clone the plugin, install dependencies and set up environment variables.

The Meshroom Hub currently hosts the following plugins:

mrBlenderSfmRenderer – Blender integration to render 3D models from multiple camera viewpoints using SfM data.
mrDeblurring – Nodes for deblurring images before reconstruction.
mrIntrinsicImageDecomposition – Separates reflectance, shading and illumination components from images.
mrGSplat – Gaussian splatting integration for Meshroom.
mrSegmentation – Segmentation and matting add-on for object isolation.
mrDepthEstimation – Monocular depth estimation nodes for 2D to depth prediction.
mrDenseMotion – Computes dense motion across video frames.
mrPhotometricStereo – Adds photometric stereo nodes for surface normal estimation.
mrRoma – Experimental node set (details not documented).
mrVideoUtils – Video and image-sequence conversion utilities.
mrGeolocation – Geolocation nodes for handling coordinate metadata.
MeshroomResearch – Collection of research nodes for prototyping and testing.
MeshroomMicMac – Nodes integrating MicMac photogrammetry tools with Meshroom.

Segmentation and targeted reconstruction

The release improves reconstruction quality through new masking and segmentation nodes. The ImageDetectionPrompt and ImageSegmentationBox nodes can generate bounding boxes from text prompts and create binary masks using the Segment Anything model. This allows targeted reconstruction, turntable object capture and merging of reconstructions from two sides. DepthMap computation times can be reduced significantly by excluding irrelevant areas, and model completeness is improved.

After segmentation analysis, Meshroom produces masks for all detectable objects in the input images. Even in complex or poorly captured data sets, or on-set reference photos, users can inspect what the algorithm recognises and directly decide which objects should be processed further. This step precedes full pipeline execution, which means that for difficult scenes or when running on weaker hardware, enormous amounts of computation time can be saved. At the same time, results can be evaluated early. The generated masks are calculated in 3D space, resulting in sharp boundaries without artefacts or bleeding. This ensures that the chosen objects are isolated with precision before dense reconstruction.

Reconstruction modes with segmentation

Meshroom 2025.1 introduces three main reconstruction modes that make use of segmentation:

Object Reconstruction inserts ImageDetectionPrompt and ImageSegmentationBox nodes parallel to SfM nodes. Segmentation masks allow focusing computation on the subject while keeping contextual surroundings if needed.

Turntable Object Reconstruction uses segmentation before feature extraction. Static backgrounds are removed early, preventing false matches and reconstruction errors.

Two-Sided Reconstruction runs two parallel reconstruction pipelines for objects photographed from opposite sides. Segmentation masks remove the background, and the two halves are then merged into one complete reconstruction.

These workflows ensure more accurate object isolation, reduce errors from background clutter and make it possible to merge multiple object views reliably.

Photometric stereo and RTI

A major addition is support for Reflectance Transformation Imaging (RTI) and Multiview Photometric Stereo. This enables reconstruction of advanced surface details with multiple light sources per viewpoint. Interactive visualisation of albedo and normal maps with real-time light control is included. A ScanRig or LightDome setup is required for full use. No other free open source solution currently offers ready-to-use Multiview Photometric Stereo. Tutorials are available for capturing datasets, but users must follow strict naming conventions (folders starting with ps_) to process images successfully.

Point clouds, Lidar and Blender preview

Experimental support for Lidar data (E57, PLY) has been added, along with meshing capabilities. The ScenePreview node allows Blender-based rendering of 3D models using SfM camera data, with support for Alembic point clouds and OBJ meshes.

Gaussian Splats/Nerfs? Yes!

Meshroom will also support Gaussian Splatting via the mrGSplat plugin. This functionality, along with other Meshroom Hub plugins, is currently available only as a developer preview, requiring the developer version of Meshroom for testing.

Development context

This 2025.1 release emerges during a period of industry-wide uncertainty in VFX and animation. Technicolor was the main Meshroom contributor, so the financial crisis at Technicolor Studios documented in February’s report (“Technicolor Studios on the Brink – MPC, The Mill, Mikros Animation at Risk“) had major consequences for the project.

MPC and The Mill are now part of the Transperfect Group and are leading the new developments in partnership with multiple research labs. More collaborators and sponsors are welcome, and those interested can find details on how to participate or donate (Donate on Paypal | GitHub Sponsorship) to the AliceVision Association.

Conclusion

Meshroom 2025.1 is not a cosmetic update. It provides production-oriented tools: reusable templates, a modular plugin system, segmentation nodes, photometric stereo, Lidar support and Blender preview. As with all new releases, users should validate stability and accuracy in test projects before adopting the update in production.

Alicevision: https://alicevision.org/

Meshroom 2025.1 on Github: https://github.com/alicevision/Meshroom/wiki/New-features-in-Meshroom-2025.1

Meshroom Github: https://github.com/alicevision/Meshroom

Meshroom Hub Github: https://github.com/meshroomHub

And here is a playlist to get you started in Meshroom!

The post Meshroom 2025.1: Templates, Plugins and Photometric Stereo first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

Anderson Rohr, known for ultra‑realistic photogrammetry assets, has gifted the Unreal Engine community a free pack of 17 scanned meshes via Fab Marketplace. Compatible with Unreal Engine 5.0–5.6, the pack includes high‑resolution textures (4K–8K) and fully functional Blueprints.

A Feast of Meshes

The pack comprises a diverse set of assets: food, decor, plants, rocks, and wood. Among the highlights are two food items—bread and chocolate panettone—alongside plant vases, ceramic figures, rocks, wood logs, crochet cacti, and more.

Texture and Material Power

Rohr has included 34 textures (Base Color, Normal, etc.) with ultra‑high resolution and material instances allowing artists to quickly adjust contrast, roughness, and specular values. The Blueprints also enable swapping of mesh tops and bottoms—such as switching between bread, rock, or wood tops.

Nanite-Enabled with No LODs

Each mesh is optimized for UE5’s Nanite technology. The pack requires no traditional LODs, thanks to Nanite’s handling of micro‑geometry. Small‑scale scene testing on moderate hardware proves viable, though users are advised to monitor GPU performance on heavier scenes Epic Developer Community Forums.

Community Gesture

Anderson Rohr releases these assets as a gesture of appreciation to the community. The pack is free, accessible on Fab.

Production Use Advice

UE artists looking to drop high‑detail scanned props into cinematic sequences, real‑time scenes, VFX setups or product visualizations can benefit from this pack. Test performance per mesh, especially with Nanite enabled; disable Nanite on problematic assets if necessary.

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Testing Reminder: Always prototype assets in your build and verify GPU performance before use in production environments.

The post Photogrammetry Parlor: Free 17-Mesh UE5 Asset Pack first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

Halon Entertainment helped preserve the world’s largest animal using LiDAR, photogrammetry, and a healthy respect for marine anatomy. We sat down with Halon’s Andrew Ritter and Jess Marley to unpack the technical choices, on-site surprises, and what it takes to turn a blue whale into a rigged digital asset ready for AR.

DP: How did Halon get involved in the Ms. Blue project?
Andrew Ritter: Jess went for a run! Right place at the right time. Jess has to tell this story himself.

Jess Marley: While visiting some of my family up in Santa Cruz, I went for an evening run and happened to sort of stumble upon Ms.Blue and the Seymour Center. I stopped in awe, took a few photos, and marvelled at her before continuing on.

I returned back to talk with my aunt Martha (who also volunteers at the center); she mentioned that some of the bones needed to come down due to safety concerns, and that Ms.Blue was pretty important to the community. Light bulb. The following morning I went back to the Seymour Center early, and with a nice fog settling in around 6:30a, perfect for scanning. Using my phone and reality scan, I spent the next 30 minutes dragging around a rickety bench, climbing on railings, and trying to cover as much of her 87ft skeleton as I could in 300 photos.

After processing that scan, exporting it to sketchfab; I then had a prototype AR (augmented reality) model which I could walk around and share. A digital double, which could likely replace her in a new digital medium. We contacted the Seymour Center, had a meeting with Jonathan and his team. The project took off. To start, we determined we would scan her, create a high resolution digital double; and then design and create two AR apps for the center.

DP: Why did you choose LiDAR scanning over traditional modeling or photogrammetry?
Jess Marley: We wanted to be as accurate as possible, and do so without damaging or removing the bones from their current position. The LiDAR is used to capture highly accurate down to the millimeter geometric information. That is paired with traditional photogrammetry photography which is then used to capture color data and reproject the whale’s texture information back onto that geometry. When captured and processed correctly, it provides stunning details which can be baked down onto lower resolution meshes used for real-time playback.

Andrew Ritter: Our goal was to end up with a multi-purpose model of the skeleton for 3D printing, AR, and digital preservation. This was LiDAR combined with photogrammetry to make sure we’d have millimeter accuracy and high resolution textures for each and every step.

DP: What was the situation “on the ground” when you arrived at the Seymour Center?
Andrew Ritter: Ms.Blue’s skeleton is fragile and mounted in place near the main museum building. It’s also outside, on the windy coast, and surrounded by landscaping. Oh and she’s the world’s largest animal at 87 feet in length…

Our capture team, Pat Surace, Tripp Topping, and Meredith Brace Sloss spent a full day scanning her from multiple locations–including from up on the museum’s roof–to ensure that we’d have what we needed once we retreated back inside.

DP: How did you prepare for the scanning pass?
Jess Marley: Due to my informal scout, we had a low resolution scan which also allowed the team to examine some of the structure prior to getting started. This gave them additional insight as to areas that might be hard to reach. So they could wisely plan their route and use their time efficently throughout the day.

Andrew Ritter: Pat Surace and Tripp Topping picked our locations and time of day based on google maps data and weather reports. By the time we show up on site, the plan’s already set, we just have to carry it out.

DP: Can you walk us through your use of the Leica RTC360 scanner?
Andrew Ritter: It’s hard to go bigger and better than the RTC360 as it’ll pull all the data accurately without having to get up close and personal. We absolutely did NOT do any crawling through Ms. Blue! And drones would require strict permits (and the cooperation of mother nature! The wind means business out there!) We briefly considered other options, but pretty quickly came to the conclusion that this was the right approach.

DP: What did your data wrangling process look like right after scanning?
Andrew Ritter: We weren’t on a strict production deadline or anything like that, so we simply downloaded the scans to an external drive and brought it back to the office. Pure capture and retreat, no on set DIT.

DP: Once back in the studio, what did your pipeline look like from raw point cloud to usable 3D asset?
Jess Marley: Processing of the LiDAR and photogrammetry went through Leica Cyclone REGISTER 360 paired with Reality Capture. A high resolution mesh with color information was then imported into Zbrush where we could sculpt and clean up any anomalies, fix any bone orientations, and add additional details lost to weathering and time. Then the process begins to fork into two paths; high resolution water tight mesh for printing, and the creation of a low resolution optimized mesh for real-time playback.

In order to print the bones, in sections we brought the high resolution mesh into CAD Fusion. This process involved a final quality check and cleanup to ensure the bones were water tight, clean, and ready for print. Those exports from Fusion were packaged up and delivered to Swellcycle.

The lower resolution mesh was decimated with some quick UVs generated, then exported from Zbrush and imported into Maya. There we refined any smaller and more intricate areas of the mesh, cleaned up UV seams and packed them in preparation for surfacing. The previous high resolution mesh and textures were then projected in Substance Painter onto the lower res asset. Additional work was then done to clean up normal artifacts and finesse the color data (while applying additional textures like roughness, metallic, gloss) to make Ms.Blue PBR ready for unity.

The last phase was to test the app and make changes based on experience. This involved adjusting and embellishing the roughness or adding some weathering in spots to generate some additional areas of interest. Once the Seymour team was happy, we delivered our final to the development team.

DP: You chose ZBrush and Substance Painter for “rebuilding” Ms. Blue. Why those tools?
Jess Marley: There’s more than one way to skin a whale. We chose to use Zbrush and Substance for a few reasons. Our pipeline supports it, and we  know both of them pretty well given our experience creating and preparing content for Unreal Engine. Efficiency and control; we had a limited budget and timeline and lots to do; plus other projects on our plate at that time. A few different artists would be shuffling on and off and sharing tasks. So the familiarity with the programs made handoff fast and easy.

DP: How did you approach digitally “repairing” the damaged bones?
Jess Marley: A combination of research, reference, and the Seymour team of scientists and their wealth of knowledge.

Andrew Ritter: Primarily research. We went back and forth with experts at Seymour and their colleagues around the world to give notes on the bones and the skinning. Sometimes it was as simple as “yeah, some teens sat on her fin in the 90s and that’s why the bones are warped. Go ahead and mirror her right fin.”

DP: How much of the animation process was grounded in science, and how much was creative liberty?
Jess Marley: We animated in traditional pose-to-pose fashion. This allowed us to animate, get feedback and refine until the team felt we had the most realistic result possible.

Andrew Ritter: The animation was very grounded in science. We were provided amazing reference footage of blue whales swimming and feeding. Stuff that has only been captured on camera in the last decade. After our passes, they’d be assessed by experts and we’d apply their notes until it was deemed as accurate as possible.

DP: Once the digital skeleton was done, what was your rigging and animation process like?
Jess Marley: Rigging was relatively simple and straightforward. An FK spine and fin system paired with blendshapes to create more complicated animations. This included a tongue, baleen, and her mouth pocket (which expands and moves a great deal while feeding).

DP: For the educational experience: Did you deliver a simple USD scene or a rigged interactive character?
Jess Marley: We packaged up a variety of rigs, props, characters, effects – all in fbx form. Once in Unity, Cavy Labs, the project’s developers were able to implement these animations into the timeline and begin on the spatial and interactive elements. The result was a series of apps for both android and iOS, accessible at the Seymour center for education and entertainment.

DP: What kind of scientific research informed those restorations?
Andrew Ritter: I have to say, we had several asset artists take passes on Ms. Blue over several months and I think they all really enjoyed it BECAUSE the notes we were getting were objective fact. The anatomical accuracy made it easy to go back and forth and nerd out between artists and scientists.

DP: Looking back, what was the most surprising challenge in the whole Ms. Blue pipeline?
Andrew Ritter: One of the most challenging aspects was actually her size. AR models are not easy to keep locked into location, and Ms. Blue has to sit atop her real-life location. We went back and forth with our developer at Cavy Labs and tried all kinds of different techniques before landing on using custom markers situated around Ms. Blue. All to keep her from swimming away…

We also set out to use this model for digital preservation and she’s already making her mark. The same assets that were used for the AR app are used for repairing the physical Ms. Blue with 3D prints and used in virtual production for news broadcasts on CBS and even shared with animators from ETC USC who needed an accurate whale skeleton for an experimental short film. I’m pretty proud that not only is this scan preserving Ms. Blue, but it’s letting her travel far and wide. Can’t imagine a better outcome than that.

DP: Are there any resources or case studies that inspired your approach or helped along the way?
Jess Marley: The team at Seymour had a plethora of research and information for us to use. We were inspired by a piece called “AR dinosaur exhibit” created by Handbuilt Creative. We had seen it while researching possibilities early on in the process (youtube.com). Tiny dinosaurs in a container environment running around in AR, going from bones to skinned. Seemed like a really good concept in relation to blending education with entertainment from our perspective. Conceptually we wanted to hit that balance.

DP: Can you share what Halon is working on next (insofar as it’s not under NDA)?
Jess Marley: As the industry seems to be shifting, we need to find new ways and avenues for work. The technology is now at everyone’s finger tips. I hope that this blend between science and entertainment becomes more regular. A lot of what we do is fun and engaging; I would love to do it on an educational level and do more teaching.

Andrew Ritter: We always jump at the chance to do projects like this with a cultural or educational impact. We certainly use these techniques in our entertainment projects, but we’re hoping that Ms. Blue’s story opens up opportunities to do more of this kind of work.

The post Skeleton Crew: How Halon Gave Ms. Blue Her Digital Bones first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

Epic Games has launched RealityScan 2.0, a comprehensive rebranding and feature update for its formerly desktop-centric photogrammetry solution, RealityCapture. The rebrand comes with a refreshed focus: mobile-first workflows, automated AI tools, and integrated support for aerial LiDAR. The move repositions the app to better serve users across industries from VFX and game development to geospatial analysis and AR/VR content creation.

From Capture to Scan: A Unified Ecosystem

The new branding consolidates Epic’s photogrammetry tools under the RealityScan name: desktop software becomes RealityScan 2.0, while the mobile companion app is now called RealityScan Mobile. Both are positioned as part of Epic’s ecosystem supporting Unreal Engine workflows.

While the underlying reconstruction engine remains based on RealityCapture technology, the update improves usability and broadens appeal beyond photogrammetry veterans. Epic’s aim: turn scanning into a faster, simpler step in asset pipelines—without sacrificing accuracy.

AI Masking: Segmentation Without the Pain

RealityScan 2.0 introduces an AI-powered segmentation tool that automatically isolates foreground objects from cluttered or textured backgrounds. A scan of fruit on a tabletop, for instance, no longer needs manual cropping or custom masking—machine learning handles the dirty work.

This AI model performs per-image semantic segmentation, making it particularly useful when scanning single assets like props or small objects. It’s a speed boost and a time-saver, especially for teams who need to generate quick scans for previz, virtual production, or rapid prototyping.

Better Alignment = Fewer Headaches

Another under-the-hood improvement: enhanced image alignment algorithms. Especially for objects with low-feature surfaces—like smooth metals or organic shapes—the updated alignment makes it easier to get stable reconstructions without constant tweaking of parameters. This shift reduces the failure rate of initial reconstructions, offering more consistent results out of the box.

LiDAR Joins the Party

Perhaps the biggest technical expansion in RealityScan 2.0 is LiDAR data integration. The software now supports combining aerial LiDAR scans with terrestrial or aerial photogrammetry—a feature previously limited to the desktop version. This makes RealityScan 2.0 applicable to a broader range of production types, including environmental reconstruction, terrain modelling, orthophoto generation, and site mapping.

During Geo Week, Epic showcased a full environment scan of Alcatraz combining aerial images and LiDAR. While niche, the workflow will appeal to studios and teams creating virtual environments or working on large-scale simulations.

Heatmaps for Mesh Confidence

RealityScan 2.0 now includes visual quality inspection tools in the form of data completeness heatmaps. These maps display sampling coverage over scanned objects, helping users identify weakly covered areas before proceeding to meshing or texturing.

This feature isn’t just cosmetic. It can prevent wasted processing time and unexpected reconstruction errors, particularly when dealing with intricate or occluded geometry. For asset teams in production, that’s a tangible win.

Real Artists, Real Feedback

Initial community responses, particularly from photogrammetry and AR developers on Reddit, suggest cautious optimism. Users welcomed the improvements in masking and alignment, though many voiced the usual caveat: these tools need to be tested before being trusted.

A Tool That Still Needs Vetting

While the update introduces smart automation and expanded formats, the core of photogrammetry hasn’t changed. Users will still need to validate mesh fidelity, texture resolution, UV cleanliness, and topology before production integration. As with all tools promising simplified workflows, RealityScan 2.0 needs a test drive in real-world conditions.

For professionals in VFX, game development, digital twins, and AR/VR, the draw is clear: faster, lighter, and more automated photogrammetry. But as always, performance matters more than promises.

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Learn more here: RealityScan

The post RealityScan 2.0: Epic Gives RealityCapture a New Name and New Tricks first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

LiDAR scanning for VFX and post-production using Leica RTC360 and RealityCapture sounds a bit technical – so let’s ask someone who has been doing exactly that, beyond some demo. Meet Lawren Bancroft-Wilson – if you’ve watched Goosebumps, The Terror or Dirk Gently’s Holistic Detective Agency, chances are you’ve seen his work—just not in a way you’d notice.

DP: Before we jump into the “how”: Can you give us the what and the why?

Lawren Bancroft-Wilson: While I’ve only been directly using LiDAR scanners on my own productions for the past 6–8 years, I’ve been working with LiDAR-derived data since the early 2000s. Even then, it was clear that anything we could receive in post that provided spatial context from set offered a major advantage—both in terms of speed and the quality of the final product.

As with all CG work, visual fidelity and believability depend on how well we can match what we build to what was actually photographed. One of the core responsibilities of the VFX team on set is to translate real-world physics into usable digital data so that artists can recreate or extend those environments with precision. LiDAR scanning lets us capture the exact geometry of the world we’re filming in, which becomes foundational for camera tracking, scene layout, and asset building.

In the same way that filming a scene is about capturing and mummifying a moment in time, LiDAR allows us to do the same with the spaces and sets we shoot in. It’s not just about documentation—it’s about freezing the physical reality of a location so it can be carried forward into every part of the VFX pipeline.

DP: So, why did you choose this model of scanner?

Lawren Bancroft-Wilson: When I’m supervising a show, speed and accuracy are the deciding factors in choosing a scanner. The window to get a scan can close in an instant—one moment you have time, and the next the AD is calling for turnover or the crew’s tearing down the set. So we needed something that could deliver high-quality results without slowing anyone down. That’s what drew me to the Leica RTC360. It can capture a full-resolution scan with photos in about 2 minutes and 42 seconds, which makes it realistic to use in the unpredictable rhythm of a real shoot day.

The only real downside is the cost of the registration software. Most VFX workflows shift to other platforms like RealityCapture once registration is done, so investing in the more expensive Leica software ecosystem is something we’ve had to weigh carefully—especially when other scanners come with simpler or cheaper options. But for our needs, the RTC360 has been worth it.

DP: When shooting a scan, do you always go for the biggest resolution?

Lawren Bancroft-Wilson: Not always. We typically go with a medium resolution and more scan positions. That gives us solid coverage without slowing things down too much. Especially on tight schedules, time is everything—and saving even a minute per scan can make the difference between getting the scan or losing the window entirely.

I always capture 360° images, and ideally, DSLR photogrammetry (or gaussian splat data) as well. That combo helps immensely in post for registration, colorizing, and photogrammetry. We concentrate scan density in areas with action or interaction, and gather broader reference when time allows. If a location will evolve across episodes, we make sure our scans overlap so we can align changes later.

Final delivery packages include .e57s, OBJs at various LODs, the original RTC files, HDRIs, photogrammetry, and any relevant art department materials.

DP: Once you have the data: How big is your storage, and how do you transfer it?

Lawren Bancroft-Wilson: Data sizes vary—from a few scans on a small set to 15–20 scans on a larger location. For a typical small set with 5–10 scans, the raw scan data usually ends up around 2 to 3 GB. That scales up quickly across multiple sets or full shooting days, so efficiency and redundancy become essential.

On set, we use the RTC360’s removable USB drives to store the raw scans. At regular intervals, we remove those USBs and back them up to encrypted NVMe SSDs using one of our VFX department laptops. We organize the file structure by episode, date, and location right away to keep everything searchable and production-aware.

From there, the data is transferred to a ZFS RAID system at our location hub, and then synced to the central VFX server at the production office. At any given time, the data exists in three places: the encrypted SSD, the location RAID, and the main VFX server. We never format or clear cards until absolutely necessary.

We deliberately keep our workflow independent of the DIT team. They’ve got their hands full with camera and colour workflows, so our team handles all scanning, backups, and asset management on our own cart.

We also use iPads on set—not only to monitor video feeds and track scan logging when we’re away from video village, but also to operate the RTC360 using Leica Cyclone FIELD 360, which lets us manage scan setups, monitor progress, and validate data capture in real time.

DP: And how much groaning does the DIT have on set?

Lawren Bancroft-Wilson: We try to keep the DIT out of it entirely—and I mean that in the kindest way. We’re great friends with our DITs and camera teams, but their workloads are already maxed out managing camera, colour, and creative requests. Adding another stream of data and logistics to their plate just isn’t fair or practical.

So we manage everything ourselves within the VFX department. That includes LiDAR, HDRIs, photogrammetry, reference photography, witness cameras and all associated backups. Our data wranglers handle all of it using our own gear and streamlined workflows.

In terms of on-set post-processing, we do a bit of early organization and preview—Lightroom for photography QC, and sometimes quick inspections of the RTC360 data using Cyclone FIELD 360 or Artec Studio to look at our Artec Leo scans. But for actual registration, we typically remote into a more powerful machine back at the office where Register 360 and other software is installed. This gives us the option to start reviewing data between wrap and the next call time, without holding up any on-set operations.

DP: How do you connect with the VFX vendors’ pipelines?

Lawren Bancroft-Wilson: We typically deliver unstructured E57s and OBJs at various levels of detail, which tend to be the most broadly supported formats across vendor pipelines—whether they’re using Houdini, Maya, Blender, Unreal, or another tool. Vendors will usually ingest those into their own systems and convert or reprocess as needed, so we focus on delivering clean, organized, and reliable source data.

We don’t enforce a standardized naming convention across vendors—each one will restructure things for their own pipeline anyway. Instead, we focus on keeping our own naming internally consistent. It may not match theirs, but it’s stable and predictable, and that makes it easy to batch convert, remap, or sync across a season. Changing separators or abbreviations mid-show can really break automated tools, so we’re careful to keep that clean.

One thing I’ve found helpful is to always include all expected folders, even if some are empty. If a folder is missing, it creates doubt—did it just not get filled, or did someone forget to include it? Including a full folder structure each time reinforces confidence in the handoff.

We maintain a clear folder structure across the full life cycle of a scan:

• Artec Leo Scans and project Files
• Leica RTC raw scan files and Register 360 project files
• E57 and LGS exports
• Epic RealityCapture scene + OBJ LODs
• Photogrammetry and DSLR imagery
• Art Dept Files
• Deliverables folder for vendors, with consolidated materials from all departments

That final vendor-ready folder combines LiDAR OBJs/E57s, HDRIs, photogrammetry, photography, and occasionally artwork or layout drawings. While we track the deeper breakdowns internally, the deliverable is kept as simple and reliable as possible on the outside.

In terms of tools, we use RealityCapture to prep and export geometry from E57s, and sometimes Blender or CloudCompare for QA or visual checks. CloudCompare has memory issues at times, but it’s still handy. Ultimately, most vendors are going to bring everything into Maya first—so as long as the data is clean and lightweight enough to open reliably, that’s the bar we aim to hit.

DP: So, when you get to the set – can you walk us through your Lidar-List?

Lawren Bancroft-Wilson: As overall supervisor, I’m often not the one doing the scans myself—that usually falls to one of our data wranglers or on-set VFX supervisors, depending on the team structure. But we treat scan days like any other shoot day: with prep, coordination, and a whole lot of communication.

Ahead of time, we’ll speak with the 2nd AD to get scanning listed on the call sheet and work with locations to secure access to spaces we might not normally reach. The locations PAs are usually briefed to help us move through the set efficiently. We also coordinate with the DP, gaffer, and key grip to understand the lighting plan, wild wall positions, and whether the set will be scanned in one configuration or several.

We try not to scan too early in the day. Often the set is still being finalized, and it’s tempting to get in there quickly, but you risk scanning a version of the set that’s going to be tweaked, blocked differently, or partially stripped out before first shot. Instead, we usually wait until a key setup is finished or during natural breaks like turnarounds, costume changes, or lunch.

Blocking is also a big factor. You may discover that what seemed like background is now in direct focus, so we try to wait until the first few takes to confirm where the action is concentrated. That informs how dense the scan coverage needs to be in different zones.

Lunch is great—if the crew goes and the lights can stay up, we can sometimes get a full scan without disrupting the schedule. But any plan to scan during lunch means speaking well ahead of time with the gaffer and key grip to make sure, if any of their team is needed to stay behind, they’re able to break early. VFX never wants to stand in the way of anyone and their well-deserved lunch.

We don’t typically place special references into the environment—at least not for LiDAR. The scanner captures what’s there, and on most sets, there’s enough unique geometry and dressing to orient the cloud. We’ll use grey and chrome balls for lighting reference, but those are captured separately and are not tied directly to the LiDAR itself.

I’ve been lucky to work with directors and DPs who really get it—who understand the value of what we’re capturing. When they do, they’re often the ones calling for quiet or holding crew so we can get the data we need. I’ve even had actors step in to help explain what’s going on when someone doesn’t realize why we’re taking a moment to scan. Not everyone knows what the LiDAR is for, but when the leadership does, it sets the tone for the whole crew.

We’re all there to create the best final product, and we’re all specialists in our own fields—knowing what we need, but still wanting to get home to our families and friends after a long day of shooting. So being respectful of what other departments need, and showing how VFX can support them too, always pays back in multiples when it’s our turn to ask for help or time.

DP: And when there is a time-constraint, because of a not-closed set, or some public access or a tsunami wave coming over the horizon: What is the “minimum viable scan” you go for?

Lawren Bancroft-Wilson: We run into this kind of situation all the time—tight windows, limited access, and not nearly enough time to get everything we’d ideally want. So when it comes down to it, we focus on scanning the areas of primary action and key camera coverage. That gives the vendors something grounded to work from and avoids a complete reliance on eyeballed matchmoves.

We also try to make sure the scans connect—if we can capture just enough locations to link the space together, even loosely, we can usually get it to register properly in post. If we know there’s going to be a return visit or the location changes over time, we’ll prioritize overlap zones to help line things up across scans.

At the same time, we’re often working in parallel—while one person handles LiDAR, another might be grabbing quick photogrammetry, or even just walking the space with an iPhone for video reference. It’s not glamorous, but that kind of continuous visual record can be a lifesaver later.

For lighting, we’ll still try to get a proper bracketed HDRI with the DSLR, but if time’s tight, we may also shoot a fast one with a 360° camera—it’s not perfect, but it’s better than nothing. The goal is to capture as much useful context as possible without slowing down the production.

And while public access or crowds aren’t usually a huge issue for us—our locations team does a great job locking things down—there’s rarely a scan where we get everything we want. So we aim for strategic coverage, get what we can, and over-communicate later so everyone knows exactly what they’re working with.

DP: When VFX-supervising during the shot, do you use additional tracking markers?

Lawren Bancroft-Wilson: To be honest, we haven’t typically used dedicated tracking markers like you’d see on larger LiDAR setups. But we’re always contending with glass and reflective surfaces. In those cases, aside from giving them a hit of AESUB Blue vanishing spray, we’ll sometimes use little squares of green camera tape across reflective areas—especially glass—to help define geometry that might otherwise go missing in the scan. That said, the RTC360 handles reflective surfaces like cars particularly well. Combining a scan with photogrammetry and Gaussian Splatting you can fill out a scan quite well.

DP: Let’s talk about the actual machine: With TSA and other agencies running amok, can you take it on a plane? And what is in your carry-on for travelling with the RTC?

Lawren Bancroft-Wilson: I’ve flown with the RTC360 a few times now, mostly between Canada and the U.S., and surprisingly, it’s been pretty smooth. TSA agents are usually curious, but not alarmed. I find it helps to explain that it’s basically a more advanced version of the LiDAR tech already built into many iPhones. That usually clicks for them, and once they hear it’s for film work, curiosity often replaces suspicion.

That said, I try to carry the scanner on with me whenever possible. I’d rather have it overhead than risk it getting bounced around or stuck in customs. The tripod usually goes into checked baggage, along with other less sensitive gear. I’ve had issues in the past with shipping, especially internationally—mismatched waybills or delays through customs clearance—so now I try to keep it on my person if I can.

For storage and transfer, we travel with a mix of encrypted SSDs and a local ZFS RAID system that stays with us on location. We also carry an iPad Pro, which we use to operate the scanner via Leica Cyclone FIELD 360, and a MacBook, which we use for backups, QC, and general scan management.

And yes, we travel with AESUB Blue vanishing spray—especially useful for scanning props with reflective surfaces like stainless steel, glass, or painted metals. It’s not cheap, but it’s one of those tools you’re glad to have when you need it.

DP: When you got everything set up: How long does the actual scanning take in your workflow? And how much effort and concentration does it take? Could an intern handle it, after the first pass?

Lawren Bancroft-Wilson: The scanner itself isn’t hard to use. The learning curve on the RTC360 is pretty manageable—most people on our team can pick it up quickly and run a basic scan. But what separates someone who can operate the scanner from someone who can really integrate it into a shoot day is the ability to read the flow of set, time it right, and communicate confidently with other departments.

That’s the real skill—not pushing the buttons, but understanding when it’s okay to hold the floor for two more minutes and how to ask for that without creating friction. It’s knowing how to stand your ground without slowing the day or rubbing anyone the wrong way.

We’ve had a mix of people handling scans on different shows—sometimes me, sometimes the on-set VFX supe, and often our data wranglers, who have been absolutely outstanding. On my last show, they had a great rapport with the crew in New York. Everyone respected the work they were doing because it was fast, precise, and never felt like a time suck. They were always present, watching the cues, ready to move when the window opened, and tracking what was done so we didn’t miss anything.

I think it’s important that everyone on the VFX team understands how to scan. Not just for redundancy, but because it builds appreciation for the challenges that come with it—and that understanding feeds back into better decisions in prep, shoot, and post.

DP: Earlier models had problems with directed IR Light sources – is that still a problem?

Lawren Bancroft-Wilson: To be honest I haven’t come across any IR light issues.

DP: Imagine a perfect world, and you are shooting with the best directors, DoPs and an unlimited budget: What would your wishlist for the perfectly Lidar-Scanning compatible set be?

Lawren Bancroft-Wilson: I’d love to scan more natural environments—beaches especially. If you gave me a week to scan a beach, I’d gladly do several tech scouts to figure out the exact time of day and conditions. Ideally, I could become the go-to choice for remote beach scanning around the world.

Sets are fun, too—but the biggest luxury would honestly just be time and space. A perfect LiDAR-compatible set isn’t necessarily about what’s built—it’s about having the freedom to access it without having to dodge crew, lighting tweaks, or production pushing forward. Give me a few hours alone with a space, and I can get you something great. That’s rarely the case in the real world, though.

I think a dream setup would be a hero location that we’re returning to multiple times throughout a show, where we’re given the chance to scan it thoroughly once, without pressure. That gives us a full base model we can build on, align to, and update with smaller detail scans as the production progresses.

So really, any set where everyone’s comfortable, there’s enough room to work, and we’re not rushed to get in and out—which is to say, no set ever.

DP: And when we look into your projects in 2035: What would you expect in features of your next-next scanner?

Lawren Bancroft-Wilson: One of my big hopes is that future LiDAR systems become even more integrated—capturing not just geometry, but lighting and color data in a way that’s accurate and production-ready, straight out of the scanner. The dream is to walk onto a location, scan it, and come back with a photorealistic digital twin that’s ready to drop into a techvis or layout workflow with minimal cleanup.

I’d love to see more computational photography integration too—leveraging the advances we’ve seen in phone cameras and neural imaging to better capture color fidelity, material surfaces, and depth in one cohesive package. Better built-in cameras on the scanner itself would help, but ideally the whole imaging and geometry pipeline gets smarter and faster. And then there’s usability. I’d want something lighter, faster, more power-efficient, and more accessible—both in price and ease of use.

But the real holy grail is how we use the data once we have it. I’d love to use LiDAR to start virtually scouting, blocking, and planning—using the captured space as a living reference for storyboarding and camera planning, maybe even from within augmented reality or wearable displays. The faster we can get from reality capture to creative application, the better.

Just recently, I attended a showcase by Sony and Pixomondo near Vancouver, BC, where they demoed their Akira system—a cutting-edge virtual production setup with precise, repeatable dolly control and an advanced motion base for vehicles, all set against beautiful LED walls running high-fidelity Unreal environments. But what really stood out came at the end of the presentation, when they previewed work involving Gaussian Splatting—capturing environments with traditional cameras and generating point clouds in just a few hours that could be pulled into Unreal Engine for techvis, previs, or even to display on an LED wall.

The potential there is huge. Being able to capture a real-world space quickly and have it usable almost immediately across multiple production tools is exactly the kind of leap we need. I think the future lies in combining high-fidelity LiDAR like the RTC360 with real-time photogrammetry or Gaussian Splatting, giving us a fast, detailed, and usable digital version of a location—without a long environment build and approval cycle. And once you factor in emerging AI tools for re-texturing, relighting, or even expanding those worlds, it feels like we’re right on the edge of something transformative for how we digitize and interact with real environments.

The post LiDAR scanning for Everybody! first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

Reality capture on mobile just got a fresh coat of machine learning. With version 3.14 of Kiri Engine, iOS users can now access AI-enhanced Lidar scanning. The photogrammetry app, previously focused on processing photos into 3D models via cloud computing, now integrates Apple’s Lidar sensor with a new AI system that promises faster and cleaner scans.

The AI enhancement isn’t just cosmetic. It automatically aligns Lidar frames into a single mesh, tackles cleanup, and handles occlusions—like fingers or accidental intrusions—without manual touch-ups. Kiri calls this the “AI Scene Construction system.” It’s designed to trim and denoise the point cloud, so users don’t have to babysit every frame.

Depth Map Meshing Joins the Party

Also new in 3.14 is depth map meshing for iOS devices with Face ID. This feature generates 3D meshes based on single-camera depth maps—ideal for devices lacking Lidar sensors. It’s not as robust as full photogrammetry or Lidar, but useful for quick object capture when time (or gear) is tight.

Works Offline—Or With the Cloud

Lidar scans are processed locally on the device, without uploading to Kiri’s servers. That makes it both faster and more private. Depth map scans, however, are still uploaded to the Kiri cloud for processing.

The iOS app supports export in OBJ, FBX, STL, and USDZ—covering most pipelines from 3D modeling to real-time applications. Android users, however, are out of luck on the Lidar and depth map features. These are iOS-only for now.

Still a Cloud-Based Photogrammetry Tool

Despite the AI upgrades, Kiri Engine’s primary function remains cloud photogrammetry: stitch together 40–70 images, get a 3D model. That workflow hasn’t changed. But the AI-assisted Lidar features now offer a quicker, more forgiving route to basic scans—handy for previs, lookdev, or blocking out geometry before committing to a full photogrammetry session.

Pricing and Availability

The Kiri Engine app is available for free on iOS and Android, with in-app purchases and subscriptions. Lidar and depth map features are exclusive to iOS. Details on pricing are available via the Kiri Engine website.

Final Note: Test Before You Commit

AI-assisted Lidar might sound like magic, but don’t swap out your tried-and-true pipeline just yet. Scan fidelity, mesh quality, and occlusion cleanup still depend on real-world lighting, surface texture, and the usual technical suspects. As always: test first, commit later.

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The post Lidar Gets a Lift: Kiri Engine 3.14 Adds AI to Its Scanning Game first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

Adobe has stirred the pot once more with the release of Substance 3D Sampler 5.0, adding a generous dash of new features to its already robust 3D material authoring and capture software.

Path Tracing in the 3D Viewport

The headline feature in this update is the introduction of path tracing within the 3D viewport. This advanced rendering technique allows artists to preview materials with greater accuracy, faithfully replicating properties such as coating, sheen, translucency, and subsurface scattering. The result? What you see is much closer to what you’ll get in the final render, reducing the guesswork and iterative tweaking.

Integration with HP’s Z Captis Material Scanner

For those with Enterprise and Teams subscriptions, Substance 3D Sampler 5.0 now offers native support for HP’s Z Captis material scanner. This integration streamlines the process of capturing real-world materials, enabling users to initiate scans directly from within the software. The captured data is automatically processed into PBR (Physically Based Rendering) channels, ready for immediate use in your projects. It’s like having a magic wand that transforms physical textures into digital assets.

Adobe Standard Material Support and Workflow Enhancements

In a move to promote consistency across applications, the update includes support for the Adobe Standard Material shader when exporting USD (Universal Scene Description) files. This ensures that materials maintain their appearance across different platforms and tools, reducing the need for tedious adjustments.

Additionally, the 3D Viewport has been enhanced with options to display shadows and reflections on the ground plane, along with a grid to indicate the scene’s origin. These visual aids provide better context during the material creation process, making it easier to position and evaluate assets.

Quick Actions and Redesigned Homepage

To further enhance usability, Adobe has introduced ‘Quick Actions’—presets that automatically populate the layer stack for common workflows. This feature accelerates the material creation process, allowing artists to jump-start their projects with predefined settings.

Pricing and Availability

Substance 3D Sampler 5.0 is available via subscription. Individual plans are offered through the Substance 3D Texturing subscription, currently priced at $19.99 per month or $219.88 per year, and the Substance 3D Collection subscription at $49.99 per month or $549.88 per year. The Linux version is accessible through the Creative Cloud for Teams subscription, priced at $1,199.88 annually.

Adobe has announced that, effective March 25, 2025, subscription prices for Substance 3D products will increase. The Substance 3D Texturing plan, which includes Substance 3D Designer, Painter, and Sampler, will rise from $19.99 to $24.99 per month, or from $219.88 to $249.88 annually. The Substance 3D Collection plan, encompassing all applications, will increase from $49.99 to $59.99 monthly, or from $549.88 to $599.88 per year. For teams, the annual subscription will go up from $1,199.88 to $1,439.88. Adobe cites continuous feature updates and product innovation as reasons for these adjustments.

As with any new software release, it’s prudent to thoroughly test these features within your existing workflow before deploying them in live projects. After all, even the most appetizing dishes benefit from a taste test before being served.

The post Adobe’s Substance 3D Sampler 5.0: Now with Path Tracing first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

FaceForm has released the latest versions of its 3D scanning tools, Wrap 2024.11 and Wrap4D 2024.11, introducing a suite of new features aimed at streamlining workflows in VFX, game development, and virtual production. These updates focus on usability, stability, and advanced functionalities tailored for high-performance pipelines. Let’s unwrap the details.

Wrap 2024.11: Node Graph Enhancements and New Tools

Wrap 2024.11 brings significant improvements to the node graph, enhancing user experience and efficiency. Users can now group nodes to organize complex graphs better, search for nodes by name to navigate large projects swiftly, and temporarily disable nodes to expedite graph evaluations. Additionally, the new SwitchGeom node allows users to toggle between input geometries, facilitating the preview of experimental changes.

The update also introduces several new nodes designed to refine the retopology process:

• SmoothGeom: Smooths high-frequency artifacts on geometry surfaces, aiding in cleaner mesh outputs.
• MirrorGeom: Mirrors geometry vertices, enabling effortless duplication during blendshape cleanup.
• TransferVertexMask: Maintains consistent vertex masks across geometries with varying topologies, ensuring uniformity in complex projects.

These additions aim to reduce manual cleanup and enhance the precision of topology transfers, though it’s advisable to test these features within your specific pipeline before full integration.

Brush Toolset Overhaul

The brush tools in Wrap have undergone a comprehensive overhaul, now optimized for tablet usage to provide a more intuitive and responsive user experience. New brush types have been added, including:

• Move Surface: Allows for intuitive manipulation of geometry surfaces.
• Relax Surface: Helps in smoothing out irregularities on the mesh.
• Mirror Clone and Clone Project: Facilitate the duplication and projection of geometry features.
• Erase: Enables precise removal of unwanted geometry details.

Additionally, the introduction of Reference Image Projection allows artists to display reference images within Wrap, serving as a guide for editing geometry. This feature is particularly beneficial for aligning 3D models with source imagery, enhancing accuracy in the modeling process.

Wrap4D 2024.11: Introducing the Blend Rig Pipeline

Wrap4D 2024.11 takes a significant leap by introducing a comprehensive Blend Rig Pipeline, a new toolset for creating and working with blendshape-based facial rigs. This pipeline allows for the generation of a blend rig from expressions and corrective blendshapes, fitting a blend rig to given geometry by optimizing controls, and exporting blend rig controls to a JSON file for easy integration into various engines.

Key nodes in this pipeline include:

• LoadBlendRig: Generates a blend rig from expressions and corrective blendshapes.
• FitBlendRig: Fits a blend rig to a given geometry by optimizing controls.
• SaveBlendRigControls: Exports blend rig controls to a JSON file, facilitating integration into different platforms.
• SmoothBlendRigControls: Prevents jittering or jumps in a blend rig control sequence, ensuring smooth animations.
• InsertBlendshapeToBlendRig: Allows adding or modifying an expression and dependent corrective blendshapes without recreating the rig, providing flexibility in rig adjustments.

This new pipeline is designed to enhance the creation and manipulation of facial rigs, offering greater control and precision in character animation. However, as with any new toolset, it’s recommended to evaluate its performance within your specific workflow to ensure compatibility and stability.

Availability and Pricing

Both Wrap 2024.11 and Wrap4D 2024.11 are available now. For detailed pricing and licensing information, visit FaceForm’s official website.

FaceForm continues to push the boundaries of 3D scanning technology, offering tools that enhance efficiency and precision in digital production. Whether you’re involved in VFX, game development, or virtual production, the latest updates to Wrap and Wrap4D provide a robust set of features designed to meet the evolving needs of the industry.

The post A Wrapping Revolution: Wrap 2024.11 & Wrap4D Unveiled first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

The latest release of PFTrack 24.12.19 from The Pixel Farm brings significant updates to its scene-reconstruction capabilities, aiming to enhance efficiency and accuracy for VFX artists. This version focuses on overhauling the photogrammetry toolset, integrating machine-learning technologies to improve performance.

AI-Powered Photogrammetry Enhancements

The Photo Survey node now features a machine-learning-based feature matching engine, designed to be faster and more accurate than previous iterations. This enhancement is expected to streamline the process of reconstructing 3D scenes from still images or video footage, reducing manual intervention and potential errors.

Lidar-Quality Point Clouds

Updates to the Point Cloud node enable the generation of point clouds with Lidar-like quality. This improvement facilitates more precise scene reconstructions, providing a solid foundation for subsequent VFX work. Additionally, new tools have been introduced for cleaning up point clouds by manually removing unwanted points, offering artists greater control over their 3D data.

Workflow and Performance Improvements

The Match Camera functionality has received workflow and performance enhancements, contributing to a more efficient match-moving process. These updates are designed to reduce the time and effort required to align virtual cameras with live-action footage, a critical task in integrating CGI elements seamlessly.

USD Workflow Updates

PFTrack 24.12.19 also includes updates to USD (Universal Scene Description) workflows, with support for point-based geometry. This addition enhances compatibility with other digital content creation tools that utilize the USD format, promoting a more integrated pipeline for complex projects.

Pricing and Availability

PFTrack operates on a rental-only model. Personal subscriptions are available at £25/month (approximately $32/month). Enterprise subscription pricing is available upon inquiry through The Pixel Farm’s website, with reseller prices listed at around $1,125/year/seat. But contact them, because we didn’t find exact prices. Also, there are rumors of a 35 Dollars per month “Personal” License, which re available as an In-App-Purchase. Resellers are (Worldwide) toolfarm.com and in Germany our friends from DVE As

Stability Considerations

While these new features offer promising enhancements, it’s advisable to test PFTrack 24.12.19 in a controlled environment before deploying it in active production. Ensuring compatibility and stability within your specific workflow can prevent potential disruptions during critical project phases. A trial version is of course available.

For a visual overview of the new features, you can watch the official release video below:

The post PFTrack 24.12.19: Scene Reconstruction Gets a Makeover first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

Pilgway has released 3DCoat 2024.30, bringing a suite of new features and improvements tailored for digital artists in VFX, game development, and CGI. This update focuses on enhancing workflow efficiency and expanding creative possibilities, all while keeping the user experience as smooth as a well-polished mesh.

Photogrammetry Integration with RealityCapture

A standout addition is the integration with RealityCapture, Epic Games’ photogrammetry software. Users can now generate 3D models from photographs or videos directly within 3DCoat, streamlining the creation of digital assets from real-world references. This feature is particularly beneficial for artists seeking to incorporate realistic textures and forms into their projects without the need for external applications.

Enhanced Volumetric Boolean Operations for 3D Printing

For those venturing into 3D printing, 3DCoat 2024.30 introduces the ability to perform volumetric boolean operations with an additional shell. This function is crucial for creating matching parts in 3D models, ensuring that components fit together seamlessly. By accessing the “Remove intersection with…” option in the SculptTree’s right-click menu, users can set up subtractions with an additional shell, facilitating the production of prototypes and complex assemblies.

New Array Tools in the Sculpt Room

The Sculpt room sees the introduction of two new tools designed to enhance modeling capabilities:

• Array Tool: Allows the creation of various arrays of volume objects along curves, enabling the efficient duplication of elements in a controlled manner. This is particularly useful for generating repetitive structures such as chains, fences, or architectural details.
• Surface Array Tool: Enables the distribution of objects across a created surface or selected faces of a low-poly mesh, providing flexibility in populating surfaces with multiple instances of an object, which can be invaluable in creating complex surface details or patterns.

Map to Mesh Conversion

In the Painting room, a new feature allows the conversion of normal maps to actual geometry. This reverse workflow enables artists to reconstruct high-poly source models from low-poly meshes adorned with normal maps. It’s particularly advantageous for refining AI-generated prototypes or enhancing existing models by adding intricate details that were initially represented only in normal maps.

Additional Enhancements

• Blender 4.2 Applink Support: The update includes support for Blender 4.2 Applink, facilitating smoother interoperability between 3DCoat and Blender, which is a boon for artists utilizing both platforms in their workflows.
• Real-Time Non-Modal Search/Filter: A new real-time search and filter function has been implemented for all item containers, including alphas, materials, objects, layers, and presets. This enhancement allows for quicker access to assets and tools, reducing downtime during the creative process.
• Improved RAW Voxel Export/Import: The RAW voxel export/import functionality has been improved to support PBR (Physically Based Rendering) data, including color, gloss, and metalness. This improvement is particularly useful for developers looking to integrate voxel data into proprietary engines while maintaining material properties.

Pricing and Availability

3DCoat 2024.30 is available for Windows, macOS, and Linux platforms. For individuals, perpetual node-locked licenses are priced at €379, with subscription options starting at €20.80 per month or €169.85 per year. Studio licenses and additional pricing details can be found on Pilgway’s official website.

Fact Check Note: While these new features enhance 3DCoat’s capabilities, it’s advisable to thoroughly test them within your specific production environment to ensure compatibility and stability before integrating them into critical workflows.

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The post 3DCoat 2024.30: New Year, New Tools for Your 3D Arsenal first appeared on DIGITAL PRODUCTION and was written by Bela Beier.