1 citations · 2 across the 8 of their papers we have counts for
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LiDAR Prompted Spatio-Temporal Multi-View Stereo for Autonomous Driving
Qihao Sun, Jiarun Liu, Ziqian Ni +5
Accurate metric depth is critical for autonomous driving perception and simulation, yet current approaches struggle to achieve high metric accuracy, multi-view and temporal consist…
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…
MipSLAM: Alias-Free Gaussian Splatting SLAM
Yingzhao Li, Yan Li, Shixiong Tian +3
This paper introduces MipSLAM, a frequency-aware 3D Gaussian Splatting (3DGS) SLAM framework capable of high-fidelity anti-aliased novel view synthesis and robust pose estimation u…
Offline-Poly: A Polyhedral Framework For Offline 3D Multi-Object Tracking
Xiaoyu Li, Yitao Wu, Xian Wu +3
Offline 3D multi-object tracking (MOT) is a critical component of the 4D auto-labeling (4DAL) process. It enhances pseudo-labels generated by high-performance detectors through the…
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.…