We are presenting today in the afternoon poster session (15:30-17:30) at Poster No. 28! #CVPR2026

The ArtiFixer code and model weights are now released! Links to both on our project page: research.nvidia.com/labs/sil… Per-scene methods like 3DGS look great on captured views but collapse off-trajectory. We repair those artifacts and beat prior SOTA by 1–3 dB PSNR. 🧵(1/6)

It’s been a while since I posted here, but I’m very excited to share what our team at @nvidia has been building over the past year! After a year of active development, we’re getting ready to release SIL-Wheel to the world: a one-stop shop platform for data-centric workflows in large-scale video model training. Built by researchers, for researchers, SIL-Wheel brings together search, curation, annotation, evaluation, and analysis for large video datasets in one centralized framework. Want a sneak peek before the official release? Come by the NeXD26 Workshop @CVPR tomorrow at 10:30!🚀

World models are moving beyond offline generation towards interactive, real-time experiences. Introducing ⚡FlashDreams⚡: an open-source high-performance inference and serving library built for autoregressive world models: 🔥 Up to 3.10× faster LingBot-World inference 🔥 Up to 2.12× faster Self-Forcing inference 🔥 Up to 1.40× faster Wan2.1 inference 🔥 8 integrated models 🔥 Multi-GPU, streaming, low-latency serving 🔥 Agentic skills that teach you how to use it FlashDreams is designed for a new generation of AI systems that continuously evolve over time while responding to user interactions. It powers applications across robotics, autonomous vehicle simulation, gaming, and virtual worlds. Github: github.com/NVIDIA/flashdream… Docs: nvidia.github.io/flashdreams Research page: research.nvidia.com/labs/sil… Join the #flashdreams Discord channel at discord.gg/yTdHDqFP FlashDreams is also the runtime backbone behind NVIDIA OmniDreams (github.com/nv-tlabs/omni-dre…) 1/n #AI #WorldModels #FastInference #PhysicalAI #OpenSource #NVIDIA

I’m excited to share what our team has been building at @NVIDIAAI since I joined: Cosmos 3, an omnimodal world model for Physical AI. Project: research.nvidia.com/labs/cos… HF: huggingface.co/collections/n… Code: github.com/NVIDIA/cosmos

Looks like I didn't do a good job of sharing this before but... Yes, you can infer, visualize, compare, train and finetune all the geometry foundation models in the MapAnything codebase‼️

Traditional 3D reconstruction pipelines like COLMAP operate in a loop, growing the scene piece-by-piece. 🧩🔄 With DejaView, we introduce this inductive bias for feed-forward 3D reconstruction—running a single alternating-attention block in a loop! Awesome work from the team 👇

📢 Stop by our #CVPR2026 workshop next week: GeoFreeNVS: Geometry-Free Novel View Synthesis and Controllable Video Models geofreenvs.github.io/ Especially excited to discuss how large generative models can solve 3D tasks like novel view synthesis!

The latent-vs-pixel debate misses the point. GPT Image 2 shows what users notice: pixel-level fidelity. Latent models show what scales: compact semantic structure. We connect them by replacing VAE/RAE decoders with a Pixel Diffusion Decoder. Code and Model available: research.nvidia.com/labs/sil… 🧵(1/N)

Exciting to share our work "Good Token Hunting" 🔍 (Yes, the name is inspired by the classic movie "Good Will Hunting" 🎬!), which focuses on accelerating visual geometry transformers 🚀 by limiting the number of keys/values each query can attend in global attention layers. [1/6]

We just released code and model! Go check it out! Code: github.com/nv-dvl/vgg-ttt Model: huggingface.co/nvidia/vgg-tt…

📢📢📢 Velox 🚀: Learning Representations of 4D Geometry and Appearance In our #CVPR2026 paper, we introduce a method for learning a native 4D representation, useful for many downstream tasks, such as video-to-4D, 3D tracking, cloth simulation, and others! 🌐: apple.github.io/ml-velox 📝: arxiv.org/abs/2605.04527

🚀We just released Asset Harvester, an image-to-3D model and end-to-end pipeline that extracts real object assets from autonomous driving videos! 🌐 Website: research.nvidia.com/labs/sil… 💻 Code: github.com/nvidia/asset-harv… [1/5] #AssetHarvester #AVSimulation #WorldModel #AutonomousDriving

We scaled up Lyra to generate explorable 3D worlds! 🚀 Introducing Lyra 2.0 — turning a single image into a 3D world you can walk through, look back, and even drop a robot into 🤖 Code and Model available today! 🌐 Website: research.nvidia.com/labs/sil… (1/N)

Introducing Neural Harmonic Textures: our new method for real-time novel view synthesis that outperforms all 3DGS and NeRF derivatives including (finally) ZipNeRF in terms of quality across all benchmarks. The code is released (Apache 2.0): (research.nvidia.com/labs/sil…) 🧵

A new generation in AV simulation is here! We are announcing AlpaDreams, a real time interactive generative world model for AV simualtion! Just a year ago it took minutes to generate a few seconds of video, today it is real time and interactive! research.nvidia.com/labs/sil…

We're releasing DiffusionHarmonizer, an online diffusion enhancer bridging neural reconstruction and photorealistic simulation by correcting artifacts, and harmonizing inserted objects so they truly belong in the scene: matching shadows, lighting & color research.nvidia.com/labs/sil…