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cs.CV2026

Lift4D: Harmonizing Single-View 3D Estimation for 4D Reconstruction In-the-Wild

Yehonathan Litman, Xiaoxuan Ma, Manan Shah +4

Reconstructing dynamic non-rigid objects from monocular video requires integrating visual cues from direct observations with data-driven priors over geometry and appearance. Prior…

cs.CV2026

REST3D: Reconstructing Physically Stable 3D Scenes from a Single Image

Xiaoxuan Ma, Jiashun Wang, Nicolas Ugrinovic +2

Reconstructing physically stable 3D scenes from a single RGB image enables casual images to be converted into simulation-ready digital assets for applications such as immersive int…

cs.CV2026

SAM 3D Body: Robust Full-Body Human Mesh Recovery

Xitong Yang, Devansh Kukreja, Don Pinkus +11

We introduce SAM 3D Body (3DB), a promptable model for single-image full-body 3D human mesh recovery (HMR) that demonstrates state-of-the-art performance, with strong generalizatio…

cs.CV2024

Purposer: Putting Human Motion Generation in Context

Nicolas Ugrinovic, Thomas Lucas, Fabien Baradel +3

We present a novel method to generate human motion to populate 3D indoor scenes. It can be controlled with various combinations of conditioning signals such as a path in a scene, t…

cs.CV2024

MultiPhys: Multi-Person Physics-aware 3D Motion Estimation

Nicolas Ugrinovic, Boxiao Pan, Georgios Pavlakos +5

We introduce MultiPhys, a method designed for recovering multi-person motion from monocular videos. Our focus lies in capturing coherent spatial placement between pairs of individu…