Pytorch-FAU

The Pytorch implementation of Facial Action Unit Intensity Estimation.

Environment

• Ubuntu 18.04.4
• Python 3.7
• PyTorch 1.3.0
• Torchvision
• Python-OpenCV

Datasets

For data preparation, please make a request for the BP4D database and the DISFA database.

Usage

The pre-trained model can be obtained from the link. Please download it under your own path. You can change default path by modifying --model_path.

• run_demo.py: visualizes the predicted AU heatmaps and intensities for the example images (data/*.jpg).

cd Pytorch-FAU/
python run_demo.py

The full code will be available soon.

Citation

@inproceedings{fan2020fau,
    title = {Facial Action Unit Intensity Estimation via Semantic 
    Correspondence Learning with Dynamic Graph Convolution},
    author = {Fan, Yingruo and Lam, Jacqueline and Li, Victor},
    booktitle = {Thirty-Fourth AAAI Conference on Artificial Intelligence},
    year={2020}
}

Acknowledgement

The code partially refers open-sourced Action-Units-Heatmaps. Thanks to them for the great work.