111 citations · 228 across the 11 of their papers we have counts for
11 papers
RCGDet3D: Rethinking 4D Radar-Camera Fusion-based 3D Object Detection with Enhanced Radar Feature Encoding
Weiyi Xiong, Bing Zhu
4D automotive radar is indispensable for autonomous driving due to its low cost and robustness, yet its point cloud sparsity challenges 3D object detection. Existing 4D radar-camer…
RadarGaussianDet3D: Gaussian Representation-based Real-time 3D Object Detection with 4D Automotive Radars
Weiyi Xiong, Bing Zhu, Zewei Zheng
4D automotive radars have gained increasing attention for autonomous driving due to their low cost, robustness, and inherent velocity measurement capability. However, existing 4D r…
ProbRadarM3F: mmWave Radar based Human Skeletal Pose Estimation with Probability Map Guided Multi-Format Feature Fusion
Bing Zhu, Zixin He, Weiyi Xiong +3
Millimeter wave (mmWave) radar is a non-intrusive privacy and relatively convenient and inexpensive device, which has been demonstrated to be applicable in place of RGB cameras in…
LiDAR Point Cloud-based Multiple Vehicle Tracking with Probabilistic Measurement-Region Association
Guanhua Ding, Jianan Liu, Yuxuan Xia +3
Multiple extended target tracking (ETT) has gained increasing attention due to the development of high-precision LiDAR and radar sensors in automotive applications. For LiDAR point…
Which Framework is Suitable for Online 3D Multi-Object Tracking for Autonomous Driving with Automotive 4D Imaging Radar?
Jianan Liu, Guanhua Ding, Yuxuan Xia +4
Online 3D multi-object tracking (MOT) has recently received significant research interests due to the expanding demand of 3D perception in advanced driver assistance systems (ADAS)…
SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar
Jianan Liu, Qiuchi Zhao, Weiyi Xiong +3
The 4D Millimeter wave (mmWave) radar is a promising technology for vehicle sensing due to its cost-effectiveness and operability in adverse weather conditions. However, the adopti…
LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion
Weiyi Xiong, Jianan Liu, Tao Huang +3
As an emerging technology and a relatively affordable device, the 4D imaging radar has already been confirmed effective in performing 3D object detection in autonomous driving. Nev…
RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection Systems
Yanlong Yang, Jianan Liu, Tao Huang +3
In autonomous driving, LiDAR and radar are crucial for environmental perception. LiDAR offers precise 3D spatial sensing information but struggles in adverse weather like fog. Conv…
GNN-PMB: A Simple but Effective Online 3D Multi-Object Tracker without Bells and Whistles
Jianan Liu, Liping Bai, Yuxuan Xia +3
Multi-object tracking (MOT) is among crucial applications in modern advanced driver assistance systems (ADAS) and autonomous driving (AD) systems. The global nearest neighbor (GNN)…
Contrastive Learning for Automotive mmWave Radar Detection Points Based Instance Segmentation
Weiyi Xiong, Jianan Liu, Yuxuan Xia +3
The automotive mmWave radar plays a key role in advanced driver assistance systems (ADAS) and autonomous driving. Deep learning-based instance segmentation enables real-time object…
Deep Instance Segmentation with Automotive Radar Detection Points
Jianan Liu, Weiyi Xiong, Liping Bai +4
Automotive radar provides reliable environmental perception in all-weather conditions with affordable cost, but it hardly supplies semantic and geometry information due to the spar…