139 citations · 205 across the 17 of their papers we have counts for
22 papers
CL3D: Unsupervised Domain Adaptation for Cross-LiDAR 3D Detection
Xidong Peng, Xinge Zhu, Yuexin Ma
Domain adaptation for Cross-LiDAR 3D detection is challenging due to the large gap on the raw data representation with disparate point densities and point arrangements. By explorin…
Weakly Supervised 3D Multi-person Pose Estimation for Large-scale Scenes based on Monocular Camera and Single LiDAR
Peishan Cong, Yiteng Xu, Yiming Ren +5
Depth estimation is usually ill-posed and ambiguous for monocular camera-based 3D multi-person pose estimation. Since LiDAR can capture accurate depth information in long-range sce…
Monocular BEV Perception of Road Scenes via Front-to-Top View Projection
Wenxi Liu, Qi Li, Weixiang Yang +5
HD map reconstruction is crucial for autonomous driving. LiDAR-based methods are limited due to expensive sensors and time-consuming computation. Camera-based methods usually need…
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes
Peishan Cong, Xinge Zhu, Feng Qiao +7
Accurately detecting and tracking pedestrians in 3D space is challenging due to large variations in rotations, poses and scales. The situation becomes even worse for dense crowds w…
LiDARCap: Long-range Marker-less 3D Human Motion Capture with LiDAR Point Clouds
Jialian Li, Jingyi Zhang, Zhiyong Wang +6
Existing motion capture datasets are largely short-range and cannot yet fit the need of long-range applications. We propose LiDARHuman26M, a new human motion capture dataset captur…
Self-supervised Point Cloud Completion on Real Traffic Scenes via Scene-concerned Bottom-up Mechanism
Yiming Ren, Peishan Cong, Xinge Zhu +1
Real scans always miss partial geometries of objects due to the self-occlusions, external-occlusions, and limited sensor resolutions. Point cloud completion aims to refer the compl…