1Beijing University of Posts and Telecommunications 2PICO IDL ByteDance
†Equal contribution *Corresponding author
🤩 Accepted to ICCV 2023
![](/zxz267/HaMuCo/raw/main/assets/HaMuCo-teaser-2.png)
HaMuCo is a multi-view self-supervised 3D hand pose estimation method that only requires 2D pseudo labels for training.
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FreiHAND evaluation code
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Multi-view inference code
[07/2023] HaMuCo is accepted to ICCV 2023 🥳!
[01/2023] Training and evaluation codes on HanCo are released.
1. Download the HanCo dataset from the official website.
- https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_rgb.zip
- https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_xyz.zip
- https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_shape.zip
- https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_calib_meta.zip
- https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_rgb_merged.zip
${ROOT}
|-- data
| |-- HanCo
| | |-- calib
| | |-- rgb
| | |-- rgb_2d_keypoints
| | |-- rgb_merged
| | |-- xyz
- Python=3.7
- PyTorch=1.9.1+cu111
- torchgeometry (need some slight changes following here.)
conda create -n hamuco python=3.7
pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
cd HaMuCo
pip install -r ./requirements.txt
If you find our work useful for your research, please consider citing the paper:
@inproceedings{
zheng2023hamuco,
title={HaMuCo: Hand Pose Estimation via Multiview Collaborative Self-Supervised Learning},
author={Zheng, Xiaozheng and Wen, Chao and Xue, Zhou and Ren, Pengfei and Wang, Jingyu},
booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
year={2023}
}
Distributed under the MIT License. See LICENSE
for more information.
The pytorch implementation of MANO is based on manopth. We thank the authors for their great job!