37 citations · 44 across the 7 of their papers we have counts for
7 papers
PvNeXt: Rethinking Network Design and Temporal Motion for Point Cloud Video Recognition
Jie Wang, Tingfa Xu, Lihe Ding +3
Point cloud video perception has become an essential task for the realm of 3D vision. Current 4D representation learning techniques typically engage in iterative processing coupled…
Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions
Jie Wang, Tingfa Xu, Lihe Ding +1
Achieving robust 3D perception in the face of corrupted data presents an challenging hurdle within 3D vision research. Contemporary transformer-based point cloud recognition models…
MsSVT++: Mixed-scale Sparse Voxel Transformer with Center Voting for 3D Object Detection
Jianan Li, Shaocong Dong, Lihe Ding +1
Accurate 3D object detection in large-scale outdoor scenes, characterized by considerable variations in object scales, necessitates features rich in both long-range and fine-graine…
Sample-adaptive Augmentation for Point Cloud Recognition Against Real-world Corruptions
Jie Wang, Lihe Ding, Tingfa Xu +4
Robust 3D perception under corruption has become an essential task for the realm of 3D vision. While current data augmentation techniques usually perform random transformations on…
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
Haiyang Wang, Lihe Ding, Shaocong Dong +5
We present a novel two-stage fully sparse convolutional 3D object detection framework, named CAGroup3D. Our proposed method first generates some high-quality 3D proposals by levera…
FusionRCNN: LiDAR-Camera Fusion for Two-stage 3D Object Detection
Xinli Xu, Shaocong Dong, Lihe Ding +3
3D object detection with multi-sensors is essential for an accurate and reliable perception system of autonomous driving and robotics. Existing 3D detectors significantly improve t…
PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds
Jie Wang, Jianan Li, Lihe Ding +2
Fine-grained geometry, captured by aggregation of point features in local regions, is crucial for object recognition and scene understanding in point clouds. Nevertheless, existing…