Shenlong Wang

SAM-V introduces a prompt-fusion mechanism that enriches sparse SAM prompt tokens with view-specific camera tokens and local VGGT features, making the prompt representation both view-aware and spatially grounded, together with a mask decoder that attends to dense 2D and 3D features.

Fire3D is a unified framework that takes a single RGB image or casual RGB video and transforms it into simulation-ready 3D scene assets for games and interactive applications in under a minute, and provides object-level completeness beyond existing feed-forward 3D approaches.

StreamForce achieves real-time video generation with physical control, outperforming traditional models in both responsiveness and realism.

Forget per-scene optimization: GenWildSplat achieves state-of-the-art 3D reconstruction from sparse, unposed images in real-time using a purely feed-forward approach.

Imagine reconstructing detailed human motion and scene layouts using just your smartwatch and earbuds – no cameras needed.

Finally, a video generation model lets you puppeteer objects and their reactions independently, all while freely moving the camera.