34 citations · 34 across the 4 of their papers we have counts for
4 papers
Bézier Degradation Modeling for LiDAR-based Human Motion Capture
Xiaoqi An, Lin Zhao, Jun Li +2
LiDAR-based 3D human motion capture has broad applications in fields such as autonomous driving and robotics, where accurate motion reconstruction is crucial. However, existing met…
Pre-training a Density-Aware Pose Transformer for Robust LiDAR-based 3D Human Pose Estimation
Xiaoqi An, Lin Zhao, Chen Gong +2
With the rapid development of autonomous driving, LiDAR-based 3D Human Pose Estimation (3D HPE) is becoming a research focus. However, due to the noise and sparsity of LiDAR-captur…
Domain adaptive pose estimation via multi-level alignment
Yugan Chen, Lin Zhao, Yalong Xu +3
Domain adaptive pose estimation aims to enable deep models trained on source domain (synthesized) datasets produce similar results on the target domain (real-world) datasets. The e…
SHaRPose: Sparse High-Resolution Representation for Human Pose Estimation
Xiaoqi An, Lin Zhao, Chen Gong +3
High-resolution representation is essential for achieving good performance in human pose estimation models. To obtain such features, existing works utilize high-resolution input im…