6 papers
AtomicMotion: Learning Human Motion From Different Human Parts
Runzhen Liu, Chuhua Xian, Fa-Ting Hong
Accurately reconstructing full-body poses from sparse head and hand trajectories is a foundational challenge for immersive AR/VR telepresence. Current methods often struggle with e…
PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects
Ziang Cao, Yinghao Liu, Haitian Li +5
Simulation-ready physical 3D assets have emerged as a promising direction owing to their broad applicability in downstream tasks. However, most existing 3D generation methods eithe…
MonoArt: Progressive Structural Reasoning for Monocular Articulated 3D Reconstruction
Haitian Li, Haozhe Xie, Junxiang Xu +3
Reconstructing articulated 3D objects from a single image requires jointly inferring object geometry, part structure, and motion parameters from limited visual evidence. A key diff…
HSImul3R: Physics-in-the-Loop Reconstruction of Simulation-Ready Human-Scene Interactions
Yukang Cao, Haozhe Xie, Fangzhou Hong +4
We present HSImul3R, a unified framework for simulation-ready 3D reconstruction of human-scene interactions (HSI) from casual captures, including sparse-view images and monocular v…
SurgCUT3R: Surgical Scene-Aware Continuous Understanding of Temporal 3D Representation
Kaiyuan Xu, Fangzhou Hong, Daniel Elson +1
Reconstructing surgical scenes from monocular endoscopic video is critical for advancing robotic-assisted surgery. However, the application of state-of-the-art general-purpose reco…
HMD^2: Environment-aware Motion Generation from Single Egocentric Head-Mounted Device
Vladimir Guzov, Yifeng Jiang, Fangzhou Hong +5
This paper investigates the generation of realistic full-body human motion using a single head-mounted device with an outward-facing color camera and the ability to perform visual…