2 citations · 2 across the 5 of their papers we have counts for
5 papers
Fusion-Poly: A Polyhedral Framework Based on Spatial-Temporal Fusion for 3D Multi-Object Tracking
Xian Wu, Yitao Wu, Xiaoyu Li +3
LiDAR-camera 3D multi-object tracking (MOT) combines rich visual semantics with accurate depth cues to improve trajectory consistency and tracking reliability. In practice, however…
Rethinking the Spatio-Temporal Alignment of End-to-End 3D Perception
Xiaoyu Li, Peidong Li, Xian Wu +7
Spatio-temporal alignment is crucial for temporal modeling of end-to-end (E2E) perception in autonomous driving (AD), providing valuable structural and textural prior information.…
RockTrack: A 3D Robust Multi-Camera-Ken Multi-Object Tracking Framework
Xiaoyu Li, Peidong Li, Lijun Zhao +5
3D Multi-Object Tracking (MOT) obtains significant performance improvements with the rapid advancements in 3D object detection, particularly in cost-effective multi-camera setups.…
Fast-Poly: A Fast Polyhedral Framework For 3D Multi-Object Tracking
Xiaoyu Li, Dedong Liu, Yitao Wu +3
3D Multi-Object Tracking (MOT) captures stable and comprehensive motion states of surrounding obstacles, essential for robotic perception. However, current 3D trackers face issues…
Poly-MOT: A Polyhedral Framework For 3D Multi-Object Tracking
Xiaoyu Li, Tao Xie, Dedong Liu +5
3D Multi-object tracking (MOT) empowers mobile robots to accomplish well-informed motion planning and navigation tasks by providing motion trajectories of surrounding objects. Howe…