9 citations · 15 across the 5 of their papers we have counts for
5 papers
DriveZero: End-to-End Driving Beyond Human Demonstrations
Hao He, Chengcheng Hu, Zirun Su +17
Most end-to-end autonomous-driving systems learn by imitating human driving logs, leaving their learned behavior constrained by the quality and behavioral coverage of the recorded…
MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Driving
Xiyang Wang, Shouzheng Qi, Jieyou Zhao +8
This paper introduces MCTrack, a new 3D multi-object tracking method that achieves state-of-the-art (SOTA) performance across KITTI, nuScenes, and Waymo datasets. Addressing the ga…
StreamMOTP: Streaming and Unified Framework for Joint 3D Multi-Object Tracking and Trajectory Prediction
Jiaheng Zhuang, Guoan Wang, Siyu Zhang +5
3D multi-object tracking and trajectory prediction are two crucial modules in autonomous driving systems. Generally, the two tasks are handled separately in traditional paradigms a…
SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving
Diankun Zhang, Guoan Wang, Runwen Zhu +15
End-to-End paradigms use a unified framework to implement multi-tasks in an autonomous driving system. Despite simplicity and clarity, the performance of end-to-end autonomous driv…
You Only Need Two Detectors to Achieve Multi-Modal 3D Multi-Object Tracking
Xiyang Wang, Chunyun Fu, Jiawei He +6
In the classical tracking-by-detection (TBD) paradigm, detection and tracking are separately and sequentially conducted, and data association must be properly performed to achieve…