DiffusionRenderer reformulates the traditional rendering process as a generative process. I am proud to be one of the main contributors to this exciting project! Hope one day this technique can be applied to game and movie production🤓

Thanks AK for sharing our GEN3C! GEN3C can easily be applied to creating video/scene from a single image, sparse-view images, or dynamic videos. Time to use video models for simulation! 🚀 Check more results: research.nvidia.com/labs/toronto-a…

Please check Chih-Hao Lin 's weather magic🤓

📢 Introducing DenseDPO: Fine-Grained Temporal Preference Optimization for Video Diffusion Models Compared to vanilla DPO, we improve paired data construction and preference label granularity, leading to better visual quality and motion strength with only 1/3 of the data. 🧵

This year, we have 3 papers in CVPR, discussing the connection between 3D and video models: GEN3C [Highlight] 3D grounding for video model DiffusionRenderer [Oral] Taming video models for rendering and inverse rendering Diffix3D+ [Oral] Enhancing Nerf/3DGS w/ diffusion models

Excited to announce our code release for DiffusionRenderer! Hope you have fun with it 😎 Catch our oral and poster presentations this Saturday afternoon at #CVPR25, Please feel free to visit!

Thanks for the invitation from Anagh Malik, DiffusionRenderer will also be presented in the poster session of the Pi3DVI Workshop (pi3dvi.github.io) tomorrow afternoon.

Excited to host Zan Gojcic talk next week on NVIDIA DiffusionRenderer, a new technique for neural rendering. It approximates how light behaves in the real world and can turn daytime scenes into night, sunny scenes into cloudy ones, and so on. It combines inverse and forward

🚀 We just open-sourced Cosmos DiffusionRenderer! This major upgrade brings significantly improved video de-lighting and re-lighting—powered by NVIDIA Cosmos and enhanced data curation. Released under Apache 2.0 and Open Model License. Try it out! 🔗 github.com/nv-tlabs/cosmo…

Following DiffusionRenderer, we made another attempt towards general-purpose relighting ✨. It can address some challenging rendering effects beyond DiffusionRenderer's capability. Please check Kai He's thread and webpage for more examples 🚀🚀🚀

NVIDIA’s AI watched 150,000 videos… and learned to relight scenes incredibly well! No game engine. No 3D software. And it has an amazing cat demo. 🐱💡 Hold on to your papers! Full video: youtube.com/watch?v=yRk6vG…

Amazing 🤩

📢 SceneComp @ ICCV 2025 🏝️ 🌎 Generative Scene Completion for Immersive Worlds 🛠️ Reconstruct what you know AND 🪄 Generate what you don’t! 🙌 Meet our speakers Angela Dai, Aleksander Holynski, Varun Jampani, Zan Gojcic Andrea Tagliasacchi 🇨🇦, Peter Kontschieder scenecomp.github.io #ICCV2025

🕹️We are excited to introduce "ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation" ChronoEdit reframes image editing as a video generation task to encourage temporal consistency. It leverages a temporal reasoning stage that denoises with “video