37 citations · 98 across the 12 of their papers we have counts for
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cs.CV2023
PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds
Hao Yang, Haiyang Wang, Di Dai +1
Pre-training is crucial in 3D-related fields such as autonomous driving where point cloud annotation is costly and challenging. Many recent studies on point cloud pre-training, how…
cs.CV2023★ 1 cited
UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation
Haiyang Wang, Hao Tang, Shaoshuai Shi +4
Jointly processing information from multiple sensors is crucial to achieving accurate and robust perception for reliable autonomous driving systems. However, current 3D perception…
cs.CV2023★ 6 cited
DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets
Haiyang Wang, Chen Shi, Shaoshuai Shi +5
Designing an efficient yet deployment-friendly 3D backbone to handle sparse point clouds is a fundamental problem in 3D perception. Compared with the customized sparse convolution,…