metadata
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 (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}
}