137 citations · 163 across the 7 of their papers we have counts for
7 papers
Doracamom: Joint 3D Detection and Occupancy Prediction with Multi-view 4D Radars and Cameras for Omnidirectional Perception
Lianqing Zheng, Jianan Liu, Runwei Guan +8
3D object detection and occupancy prediction are critical tasks in autonomous driving, attracting significant attention. Despite the potential of recent vision-based methods, they…
MetaOcc: Spatio-Temporal Fusion of Surround-View 4D Radar and Camera for 3D Occupancy Prediction with Dual Training Strategies
Long Yang, Lianqing Zheng, Wenjin Ai +8
Robust 3D occupancy prediction is essential for autonomous driving, particularly under adverse weather conditions where traditional vision-only systems struggle. While the fusion o…
OmniHD-Scenes: A Next-Generation Multimodal Dataset for Autonomous Driving
Lianqing Zheng, Long Yang, Qunshu Lin +10
The rapid advancement of deep learning has intensified the need for comprehensive data for use by autonomous driving algorithms. High-quality datasets are crucial for the developme…
TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving
Lianqing Zheng, Zhixiong Ma, Xichan Zhu +9
The next-generation high-resolution automotive radar (4D radar) can provide additional elevation measurement and denser point clouds, which has great potential for 3D sensing in au…
A Learning-based Stochastic Driving Model for Autonomous Vehicle Testing
Lin Liu, Shuo Feng, Yiheng Feng +2
In the simulation-based testing and evaluation of autonomous vehicles (AVs), how background vehicles (BVs) drive directly influences the AV's driving behavior and further impacts t…
A Gradual Takeover Strategy of the Active Safety System
Rui Liu, Xichan Zhu, Xuan Zhao +1
A gradual takeover strategy is proposed, in which the dynamic driving privilege assignment in real-time and the driving privilege gradual handover are realized. Firstly, the drivin…
Statistical Characteristics of Driver Acceleration Behavior and Its Probability Model
Rui Liu, Xuan Zhao, Xichan Zhu +1
Naturalistic driving data were applied to study driver acceleration behaviour, and a probability model of the driver was proposed. First, the question of whether the database is la…