8 citations · 16 across the 6 of their papers we have counts for
6 papers · 1 filter
Scaling Multi-Camera 3D Object Detection through Weak-to-Strong Eliciting
Hao Lu, Jiaqi Tang, Xinli Xu +6
The emergence of Multi-Camera 3D Object Detection (MC3D-Det), facilitated by bird's-eye view (BEV) representation, signifies a notable progression in 3D object detection. Scaling M…
GraphAD: Interaction Scene Graph for End-to-end Autonomous Driving
Yunpeng Zhang, Deheng Qian, Ding Li +11
Modeling complicated interactions among the ego-vehicle, road agents, and map elements has been a crucial part for safety-critical autonomous driving. Previous works on end-to-end…
3DSFLabelling: Boosting 3D Scene Flow Estimation by Pseudo Auto-labelling
Chaokang Jiang, Guangming Wang, Jiuming Liu +6
Learning 3D scene flow from LiDAR point clouds presents significant difficulties, including poor generalization from synthetic datasets to real scenes, scarcity of real-world 3D la…
Detecting As Labeling: Rethinking LiDAR-camera Fusion in 3D Object Detection
Junjie Huang, Yun Ye, Zhujin Liang +2
3D object Detection with LiDAR-camera encounters overfitting in algorithm development which is derived from the violation of some fundamental rules. We refer to the data annotation…
OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction
Yunpeng Zhang, Zheng Zhu, Dalong Du
The vision-based perception for autonomous driving has undergone a transformation from the bird-eye-view (BEV) representations to the 3D semantic occupancy. Compared with the BEV p…
OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception
Xiaofeng Wang, Zheng Zhu, Wenbo Xu +7
Semantic occupancy perception is essential for autonomous driving, as automated vehicles require a fine-grained perception of the 3D urban structures. However, existing relevant be…