https://github.com/cvi-szu/mdhr
Code for paper multi-scale dynamic and hierarchical relationship modeling for facial action units recognition
Science Score: 23.0%
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○CITATION.cff file
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○Scientific vocabulary similarity
Low similarity (8.2%) to scientific vocabulary
Repository
Code for paper multi-scale dynamic and hierarchical relationship modeling for facial action units recognition
Basic Info
- Host: GitHub
- Owner: CVI-SZU
- License: mit
- Language: Python
- Default Branch: main
- Size: 2.86 MB
Statistics
- Stars: 29
- Watchers: 3
- Forks: 0
- Open Issues: 6
- Releases: 0
Metadata Files
README.md
[CVPR2024]
Multi-Scale Dynamic and Hierarchical Relationship Modeling for Facial Action Units Recognition
This is an official release of the Paper.
Overview:
Requirements
- Python3
- PyTorch
bash
pip install -r requirements.txt
Training
bash
python train.py --backbone resnet --fold 1 --dataset_path /path/to/BP4D_dataset/
Testing
bash
python test_BP4D.py --backbone resnet --fold 1 --dataset_path /path/to/BP4D_dataset/ --resume /path/to/best_model_fold1.pth --evaluate
results
BP4D
DISFA
Citation
if the code or method help you in the research, please cite the following paper: ```bash @article{wang2024multi, title={Multi-scale Dynamic and Hierarchical Relationship Modeling for Facial Action Units Recognition}, author={Wang, Zihan and Song, Siyang and Luo, Cheng and Deng, Songhe and Xie, Weicheng and Shen, Linlin}, journal={arXiv preprint arXiv:2404.06443}, year={2024} }
@inproceedings{wang2023spatial, title={Spatial-temporal graph-based AU relationship learning for facial action unit detection}, author={Wang, Zihan and Song, Siyang and Luo, Cheng and Zhou, Yuzhi and Wu, Shiling and Xie, Weicheng and Shen, Linlin}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={5899--5907}, year={2023} }
@inproceedings{luo2022learning, title = {Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognition}, author = {Luo, Cheng and Song, Siyang and Xie, Weicheng and Shen, Linlin and Gunes, Hatice}, booktitle = {Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, {IJCAI-22}}, pages = {1239--1246}, year = {2022} } ```
Acknowledgements
This repo is built using components from ME-GraphAU
Owner
- Name: Computer Vision Institute, SZU
- Login: CVI-SZU
- Kind: organization
- Location: Shenzhen Univeristy, Shenzhen, China
- Website: http://cv.szu.edu.cn/
- Repositories: 13
- Profile: https://github.com/CVI-SZU
Computer Vision Institute, Shenzhen University
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