23 citations · 45 across the 6 of their papers we have counts for
7 papers · 1 filter
Learning Variational Motion Prior for Video-based Motion Capture
Xin Chen, Zhuo Su, Lingbo Yang +4
Motion capture from a monocular video is fundamental and crucial for us humans to naturally experience and interact with each other in Virtual Reality (VR) and Augmented Reality (A…
Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions
Guoxing Sun, Xin Chen, Yizhang Chen +6
4D reconstruction of human-object interaction is critical for immersive VR/AR experience and human activity understanding. Recent advances still fail to recover fine geometry and t…
Few-shot Neural Human Performance Rendering from Sparse RGBD Videos
Anqi Pang, Xin Chen, Haimin Luo +3
Recent neural rendering approaches for human activities achieve remarkable view synthesis results, but still rely on dense input views or dense training with all the capture frames…
SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos
Xin Chen, Anqi Pang, Wei Yang +3
Markerless motion capture and understanding of professional non-daily human movements is an important yet unsolved task, which suffers from complex motion patterns and severe self-…
ChallenCap: Monocular 3D Capture of Challenging Human Performances using Multi-Modal References
Yannan He, Anqi Pang, Xin Chen +4
Capturing challenging human motions is critical for numerous applications, but it suffers from complex motion patterns and severe self-occlusion under the monocular setting. In thi…
AutoSweep: Recovering 3D Editable Objectsfrom a Single Photograph
Xin Chen, Yuwei Li, Xi Luo +4
This paper presents a fully automatic framework for extracting editable 3D objects directly from a single photograph. Unlike previous methods which recover either depth maps, point…