activity
20222024
most citedOccluded Human Body Capture with Self-Supervised Spatial-Temporal Motion Prior

4 citations · 7 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024

Closely Interactive Human Reconstruction with Proxemics and Physics-Guided Adaption

Buzhen Huang, Chen Li, Chongyang Xu +3

Existing multi-person human reconstruction approaches mainly focus on recovering accurate poses or avoiding penetration, but overlook the modeling of close interactions. In this wo…

cs.CV20231 cited

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…

cs.CV20232 cited

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…

cs.CV2023

Nonrigid Object Contact Estimation With Regional Unwrapping Transformer

Wei Xie, Zimeng Zhao, Shiying Li +2

Acquiring contact patterns between hands and nonrigid objects is a common concern in the vision and robotics community. However, existing learning-based methods focus more on conta…

cs.CV2023

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…

cs.CV2023

Semi-supervised Hand Appearance Recovery via Structure Disentanglement and Dual Adversarial Discrimination

Zimeng Zhao, Binghui Zuo, Zhiyu Long +1

Enormous hand images with reliable annotations are collected through marker-based MoCap. Unfortunately, degradations caused by markers limit their application in hand appearance re…