qq456cvb/CanonicalVoting

Canonical Voting: Pretrained Models

Pretrained models for Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes (CVPR 2022).

Paper: arXiv:2011.12001 · Hugging Face paper page

Code: https://github.com/qq456cvb/CanonicalVoting

Project page: https://qq456cvb.github.io/projects/canonical-voting

Processed data and annotations: https://huggingface.co/datasets/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}
}