Papers › CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
Haiyang Wang, Lihe Ding, Shaocong Dong, Shaoshuai Shi, Aoxue Li, Jianan Li, Zhenguo Li, LiWei Wang
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 leveraging the class-aware local group strategy on the object surface voxels with the same semantic predictions, which considers semantic consistency and diverse locality abandoned in previous bottom-up approaches. Then, to recover the features of missed voxels due to incorrect voxel-wise segmentation, we build a fully sparse convolutional RoI pooling module to directly aggregate fine-grained spatial information from backbone for further proposal refinement. It is memory-and-computation efficient and can better encode the geometry-specific features of each 3D proposal. Our model achieves state-of-the-art 3D detection performance with remarkable gains of +\textit{3.6\%} on ScanNet V2 and +\textit{2.6}\% on SUN RGB-D in term of mAP@0.25. Code will be available at https://github.com/Haiyang-W/CAGroup3D.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Object Detection | SUN-RGBD | CAGroup3D (Geo Only) | mAP@0.25 | 66.8 | #2 of 8 | Archive leaderboard | report |
| 3D Object Detection | SUN-RGBD | CAGroup3D (Geo Only) | mAP@0.5 | 50.2 | #2 of 8 | Archive leaderboard | report |
| 3D Object Detection | SUN-RGBD val | CAGroup3D(Geo only) | mAP@0.25 | 66.8 | #8 of 32 | Archive leaderboard | report |
| 3D Object Detection | SUN-RGBD val | CAGroup3D(Geo only) | mAP@0.5 | 50.2 | #8 of 32 | Archive leaderboard | report |
| 3D Object Detection | ScanNetV2 | CAGroup3D | mAP@0.25 | 75.1 | #9 of 33 | Archive leaderboard | report |
| 3D Object Detection | ScanNetV2 | CAGroup3D | mAP@0.5 | 61.3 | #9 of 33 | Archive leaderboard | report |
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