12 citations · 20 across the 6 of their papers we have counts for
6 papers
Simultaneously Recovering Multi-Person Meshes and Multi-View Cameras with Human Semantics
Buzhen Huang, Jingyi Ju, Yuan Shu +1
Dynamic multi-person mesh recovery has broad applications in sports broadcasting, virtual reality, and video games. However, current multi-view frameworks rely on a time-consuming…
CrowdRec: 3D Crowd Reconstruction from Single Color Images
Buzhen Huang, Jingyi Ju, Yangang Wang
This is a technical report for the GigaCrowd challenge. Reconstructing 3D crowds from monocular images is a challenging problem due to mutual occlusions, server depth ambiguity, an…
Reconstructing Groups of People with Hypergraph Relational Reasoning
Buzhen Huang, Jingyi Ju, Zhihao Li +1
Due to the mutual occlusion, severe scale variation, and complex spatial distribution, the current multi-person mesh recovery methods cannot produce accurate absolute body poses an…
Physics-Guided Human Motion Capture with Pose Probability Modeling
Jingyi Ju, Buzhen Huang, Chen Zhu +2
Incorporating physics in human motion capture to avoid artifacts like floating, foot sliding, and ground penetration is a promising direction. Existing solutions always adopt kinem…
Occluded Human Body Capture with Self-Supervised Spatial-Temporal Motion Prior
Buzhen Huang, Yuan Shu, Jingyi Ju +1
Although significant progress has been achieved on monocular maker-less human motion capture in recent years, it is still hard for state-of-the-art methods to obtain satisfactory r…
Neural MoCon: Neural Motion Control for Physically Plausible Human Motion Capture
Buzhen Huang, Liang Pan, Yuan Yang +2
Due to the visual ambiguity, purely kinematic formulations on monocular human motion capture are often physically incorrect, biomechanically implausible, and can not reconstruct ac…