For those who don’t know the format: DNG is a RAW file container that sits between camera capture and post, showing up in ingest, transcode, grading, VFX pulls, and archive handoff, with a spec now mirrored by ISO 12234-4:2026.

The boring news that makes pipelines happier

DNG (Which stands for “Digital NeGative”, as someone surely learned and realised just now for the first time. If it’s you: Hi!!!!! ) now has an International Standard that specifies the file format. The published document is ISO 12234-4:2026 (Catchy….) , titled Digital imaging, Image storage, Part 4, Digital negative format. The standard is Edition 1, dated 2026-03, and about 100 riveting pages. The publication stage shows the International Standard published on 2026-03-24. But why shoud you care?

In plain pipeline terms, a file format spec moving into an ISO standard gives studios, vendors, and archives something concrete to point at when they need to define what a deliverable is. Not a vibe, not a promise, not a forum thread. A document.

A format grows up and gets paperwork

The DNG story did not start with a standards committee. The format was announced in September 2004. The goal at launch positioned DNG as an open and fully documented alternative to a growing set of proprietary RAW formats. The standardisation track has its own dates. The ISO 12234-4 project shows approval in February 2023, and a committee draft registered in June 2024. The publication stage lands in March 2026. Multiple draft stages existed, ballots ran, and a final publication date appears in the standard life cycle. Even if you never read page one, the existence of a defined life cycle is part of what procurement and preservation teams actually buy into.

We have to talk about CinemaDNG

Now, as great as all that is: CinemaDNG, the “Moving Pictures” Variant, a container with DNGs in it, is not on a roadmap to become an open Standard in the foreseeable future. Eventually someone will hopefully take pity, or there will be just one camera vendor left (Place your bets, ladies and gents….)

So, in that area, we still have ArriRAW, Braw, SonyRAW, CanonRAW, ProresRAW, PhantomRAW, RedRAW, RealRAW and are raw-ring (Bad pun, sorry) for a file standard that would be usable, free of problematic vendor choices (Not generally free, just not … problematic), and would just work. Excuse the outburst, back to the topic at hand. And yes, one of those formats is an invention, did you spot which one? It is April 1st after all.

What changes for post, VFX, and archive

Camera RAW formats tend to be popular because they keep options open for creative control, but they also create a dependency problem when specifications are not publicly available. If only one manufacturer’s toolchain can reliably read a file, long term access becomes a risk, and sharing across complex pipelines becomes harder.

DNG is now a publicly available archival format for raw files generated by various digital cameras. The format addresses the lack of an open standard for raw files created by individual camera models and aims to ensure photographers, filmmakers, and everybody doing pretty pictures can access their files.

An ISO document specifying the file froamt also gives asset managers a clearer way to define what they want to store. If you need to archive camera originals, mezzanine intermediates, and extracted plates, you often end up fighting two battles at once: what the pixels are, and what the metadata contract is. A formally specified container does not solve every metadata debate, but it does reduce the number of arguments that start with what even is this file.

Another practical shift is the language used in institutional workflows. Policies and contracts like standards. Long term storage systems like standards. Deliverable checklists like standards. Having ISO 12234-4:2026 on the shelf means teams can reference a published International Standard when they specify interoperable RAW formats for capture, ingest, transcode, management, and archiving.

TIFF roots, modern expectations

DNG did not appear in a vacuum. The format was built on the foundation of ISO 12234-2:2001, which specifies TIFF/EP-images. If your pipeline already has tooling that understands TIFF style containers (*Cough* print….) and robust tag handling, that heritage can be one reason DNG keeps showing up as a bridge format in real shops. The standardisation step does not magically turn every camera into a DNG camera, but it does make the file description less dependent on any single ecosystem narrative. Adobe, which invented the format, has useful and quite robust free converters for Mac & Windows: https://helpx.adobe.com/camera-raw/digital-negative.html

A reminder before you rewrite your whole ingest plan

Standards are comforting, but pipelines are still pipelines. Test any new tool or workflow change before you put it into production, especially where RAW ingest, transcoding, and archive validation sit on the critical path. A shiny standard does not replace practical verification; it just makes the target less fuzzy.

And if your team has already been treating DNG as a useful interchange or archival option, the big difference now is that the file format sits within an ISO publication path with dates, editioning, and a stable identifier.

https://www.iso.org/obp/ui/en/#iso:std:iso:12234:-4:ed-1:v1:en

https://www.iso.org/standard/86123.html

https://www.iso.org/standard/29377.html

The post Adobe DNG becomes ISO standard (Not an April Fools joke) first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

For those who don’t know the tool: glTF sits between DCC export and runtime playback, and these web tools help you sanity check assets and rendering across engines before shots get spicy.

Two sites, one mission: fewer surprises

The glTF Sample Assets site and the glTF Render Fidelity Comparison site just got meaningful upgrades. They target the same everyday pain: you export a model, it looks right in one viewer, and then it looks slightly off somewhere else where it matters. The refreshed Sample Assets experience focuses on browsing, filtering, and sharing reference models that exercise specific features of glTF. The updated Render Fidelity Comparison experience focuses on visual baselines, with side-by-side checks that make renderer differences harder to hand wave and easier to track down. If you build tools, ship engines, validate exporters, or wrangle assets for realtime and VFX, these sites are designed to be the boring, reliable kind of helpful.

Sample Assets gets a real front door

The new landing experience for glTF Sample Assets presents the repository as a proper website. The intent is simple: make it easier to browse and find models by what they demonstrate. Models appear with thumbnails, and animated assets include a small animation preview. The site supports light and dark themes and aims for fast loading and fluid navigation. Filtering and search are first class, with tags that map to features, functionality, and extension coverage.

When you open a model, you land on a dedicated model page with an interactive preview, metadata, and download links. The preview uses the glTF Sample Renderer, which is built on WebGL and targets correct support for official KHR extensions. A context menu in the preview provides presentation options that include debug visualization modes for material properties, variant selection when multiple variants exist, and wireframe presentation when the WEBGL polygon mode extension is available.

The model page also links out to external tools and shows a recommendation style list of related assets, which is a surprisingly effective way to bounce between test cases when you are chasing a specific shading edge case across multiple files.

One practical detail matters here: each model includes a screenshot, description, license information, and a live preview. That combination turns the site into a quick reference shelf rather than a scavenger hunt through folders.

Render Fidelity Comparison leans into side by side truth

The redesigned glTF Render Fidelity Comparison site takes the same library mindset and aims it at output consistency. It frames the core goal as convergence around physically based rendering materials so you can expect a model to appear as intended across renderers and lighting environments. It also notes that this is ambitious, with realtime rendering quality still changing rapidly. *cough* understatement *cough*

The workflow is built for quick comparisons. You choose a model, filter by tags or search, then pick two renders and select a view mode. The comparison modes include side by side viewing, a slider view, and a difference view that shows computed differences.

The site spans popular realtime web renderers and also includes path tracers. In practice, that means you can jump between quick interactive engines like babylon.js and three.js, then also look at path traced production renderings from Blender using Cycles and from V-Ray. It is not about crowning a winner. It is about seeing where two implementations diverge so you can reproduce, triage, and fix.

Comparison images are generated offline and submitted via pull requests to the site repository, which keeps the content auditable and repeatable. That approach also makes it easier for teams to add coverage for their own renderer outputs without inventing a new pipeline.

The biggest new trick is an experimental 3D comparison mode that enables full interactivity comparison of two realtime renderers side by side. It currently supports three.js, babylon.js, model-viewer, and three js path tracer tooling. If you have ever tried to discuss a subtle lighting mismatch over screenshots, you know why interactive side by side matters. In one sentence, the updated site encourages you to comapre outputs with fewer assumptions and more pixels on screen.

https://github.khronos.org/glTF-Render-Fidelity/model/AttenuationTest

Contributing is part of the design

Both sites are open to contributions. For sample assets, new models can be proposed via pull requests to the repository. For render fidelity, you can submit renderer outputs by following the repository guidelines for generating renders of a sample asset and placing the results in the appropriate location for comparison.

There is also a straightforward feedback loop via issues in the repositories, which keeps bug reports and feature requests attached to something actionable. This is the one place where it is worth naming the organizer exactly once: Khronos is clearly aiming to make the glTF developer ecosystem easier to navigate, easier to test, and harder to break quietly.

https://github.khronos.org/glTF-Assets/

https://github.khronos.org/glTF-Render-Fidelity/

The post glTF sample assets and fidelity site refresh first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

For those who don’t know the Smpte: The Society of Motion Picture and Television Engineers (SMPTE) sets the technical standards behind nearly everything that moves on a screen. From colorimetry to file formats, SMPTE defines the backbone of professional workflows in postproduction, broadcast, and digital cinema. Their new engineering report Artificial Intelligence and Media (ER 1011:2025) updates the 2023 edition with the latest thinking on AI, and is freely available to non-members.

Open source and open AI

The first section revisits the foundations of machine learning and deep learning, before expanding into what SMPTE now calls “open source artificial intelligence”. The report clarifies the difference between open-weight and truly open source AI, where not just the model weights, but also code, data, and documentation are publicly accessible. It also points to the emerging concept of Responsible AI Licenses and frameworks like the Model Openness Framework (MOF). SMPTE notes that “open-washing”, marketing closed systems as open, is a growing issue engineers must recognise.

Generative models and interoperability

A substantial chapter examines generative AI, from diffusion models and GANs to LLMs and multimodal architectures capable of handling text, sound, image, and video simultaneously. The report highlights the growing influence of protocols like the Model Context Protocol (MCP) and Google’s A2A for agent-to-agent interoperability, described as the foundation for “agentic workflows.” SMPTE sees these protocols as key to connecting intelligent tools in post and broadcast environments, without locking developers into single ecosystems.

Security, ethics, and regulation

Security receives dedicated attention. SMPTE warns of risks such as data poisoning, jailbreaking, and intellectual property leakage within AI-driven workflows. The report advocates Zero Trust Architectures (as defined by MovieLabs), calling for authentication and authorisation mechanisms even between AI agents. The ethics chapter, meanwhile, argues that AI in media must be both transparent and auditable “because failing is expensive, and media needs its own voice.” It outlines principles of inclusivity, transparency, and fit-for-purpose design, forming what SMPTE calls the “AI Ethics Pipeline”.

Standards and data: the next frontier

In its closing chapters, the report maps the AI standards landscape, noting gaps around ontologies, benchmarking, and model metadata. The authors identifie opportunities for collaboration with the EBU, ISO/IEC, and other bodies, stressing the need for shared datasets to train and validate media-specific AI systems. These datasets, the report says, are crucial for reproducible research and safe deployment in production pipelines. As always, SMPTE closes with a reminder that technology, especially AI, must prove itself in real-world conditions before being trusted in production.

The full Engineering Report ER 1011:2025 – Artificial Intelligence and Media is available for free download from the SMPTE website. It is dense, detailed, and refreshingly un-hyped. A technical must-read for anyone designing, coding, or approving AI-assisted tools in post, broadcast, or digital cinema. Before your next machine learning experiment runs in production, take an hour to read what SMPTE’s engineers have already tested and defined.

The post SMPTE updates its AI report: a roadmap for media engineers first appeared on DIGITAL PRODUCTION and was written by Bela Beier.

Trimble has released SketchUp 2025, introducing real-time photorealistic materials that dynamically react to lighting conditions. These materials feature physically based reflectivity, transparency, and roughness, allowing users to preview real-world material behavior without requiring an external renderer. The update affects all SketchUp editions, including Desktop, Web, and iPad.

Environment Lighting with HDRI and EXR

Lighting simulation has also improved: SketchUp now supports 360-degree HDRI and EXR images as light sources. Instead of relying on generic ambient lighting, users can import high-dynamic-range images to simulate realistic environmental lighting, enhancing material realism. The feature is available across the SketchUp ecosystem, including LayOut.

Ambient Occlusion for More Depth

Another key addition is ambient occlusion, a shading technique that increases depth perception by simulating how light interacts with corners and edges. Even when no materials are applied, ambient occlusion improves model clarity, making it easier to interpret spatial relationships in architectural and industrial designs.

Expanded Interoperability and File Support

SketchUp 2025 further refines Revit and IFC file integration, allowing for more predictable IFC roundtrips and enhanced control over which Revit elements are imported. The update also improves USD and glTF export, now with support for photorealistic materials. This makes SketchUp more compatible with visualization pipelines that use real-time engines like Unreal Engine and Unity.

Updated 3D Warehouse and LayOut Workflow

3D Warehouse has been expanded with curated photoreal materials, environments, and configurable 3D assets, reducing the need to create assets from scratch. Meanwhile, LayOut’s UX has been updated to improve consistency with SketchUp’s interface, providing a smoother document creation experience.

Pricing and Availability

SketchUp 2025 is compatible with Windows 10+ and macOS 12.0+. It is available as a subscription-based service:

• SketchUp Go (browser + iPad) – $119/year
• SketchUp Pro (desktop + LayOut) – $349/year
• SketchUp Studio (full suite) – $749/year
• SketchUp Free (web-based, feature-limited) – Free

Final Thoughts

SketchUp 2025 delivers a noticeable leap in visual realism and interoperability. While it doesn’t replace dedicated render engines, the real-time material and lighting previews provide faster, more informed design decisions. As always, test these new features thoroughly before integrating them into your workflow.

The post SketchUp 2025: Better Visuals, Smoother Workflows first appeared on DIGITAL PRODUCTION and was written by Bela Beier.