226 citations · 519 across the 24 of their papers we have counts for
48 papers
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…
Towards 3D Scene Understanding by Referring Synthetic Models
Runnan Chen, Xinge Zhu, Nenglun Chen +5
Promising performance has been achieved for visual perception on the point cloud. However, the current methods typically rely on labour-extensive annotations on the scene scans. In…
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perception
Xinge Zhu, Hui Zhou, Tai Wang +6
State-of-the-art methods for driving-scene LiDAR-based perception (including point cloud semantic segmentation, panoptic segmentation and 3D detection, \etc) often project the poin…
Detailed Avatar Recovery from Single Image
Hao Zhu, Xinxin Zuo, Haotian Yang +3
This paper presents a novel framework to recover \emph{detailed} avatar from a single image. It is a challenging task due to factors such as variations in human shapes, body poses,…
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
Yulong Cao*, Ningfei Wang*, Chaowei Xiao* +6
In Autonomous Driving (AD) systems, perception is both security and safety critical. Despite various prior studies on its security issues, all of them only consider attacks on came…
Semantic Distribution-aware Contrastive Adaptation for Semantic Segmentation
Shuang Li, Binhui Xie, Bin Zang +4
Domain adaptive semantic segmentation refers to making predictions on a certain target domain with only annotations of a specific source domain. Current state-of-the-art works sugg…