| license: mit | |
| tags: | |
| - 3d-object-detection | |
| - point-cloud | |
| - scannet | |
| - sun-rgbd | |
| # Canonical Voting: Pretrained Models | |
| Pretrained models for [Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes](https://openaccess.thecvf.com/content/CVPR2022/html/You_Canonical_Voting_Towards_Robust_Oriented_Bounding_Box_Detection_in_3D_CVPR_2022_paper.html) (CVPR 2022). | |
| Code: https://github.com/qq456cvb/CanonicalVoting | |
| ## Files | |
| | File | Description | | |
| | --- | --- | | |
| | `scannet/joint.pth` | Jointly trained model for all categories on ScanNet (~15.4 mAP) | | |
| | `scannet/separate/<wordnet_id>.pth` | Separately trained per-category models on ScanNet (~21.7 mAP overall) | | |
| | `sunrgbd/checkpoint.pth` | Pretrained CanonicalVoting model for SUN RGB-D (used with BRNetCanon) | | |
| Per-category ScanNet models cover wordnet ids `02747177`, `02808440`, `02871439`, `02933112`, `03001627`, `03211117`, `04256520`, `04379243`, plus `others`. | |
| ## Citation | |
| ``` | |
| @inproceedings{you2022canonical, | |
| title={Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes}, | |
| author={You, Yang and Ye, Zelin and Lou, Yujing and Li, Chengkun and Li, Yong-Lu and Ma, Lizhuang and Wang, Weiming and Lu, Cewu}, | |
| booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, | |
| pages={1193--1202}, | |
| year={2022} | |
| } | |
| ``` | |