ARBEx: Attentive Feature Extraction with Reliability Balancing for Robust Facial Expression Learning

Azmine Toushik Wasi*, Karlo Serbetar*, Raima Islam*, Taki Hasan Rafi*, and Dong-Kyu Chae

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For any questions, please contact to : takihr@hanyang.ac.kr

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Architecture

Pipeline of ARBEx.

Setup and run

Put pretrained ir50.pth and mobilefacenet.pth into arbex/models/pretrained. By default, data is assumed to be in ../../_DATA. The code assumes AffWild2 as the default dataset here. If you intend to use other datasets, you may need to make certain changes in the data loading process, in arbex/data.py. To change the default paths, change DIR_IMG, DIR_ANN_TRAIN, DIR_ANN_DEV in arbex/config.py To install the dependencies run:

pip install -r requirements.txt

To run the training script:

python train.py

Working Principle

Citation

@misc{wasi2023arbex,
      title={ARBEx: Attentive Feature Extraction with Reliability Balancing for Robust Facial Expression Learning}, 
      author={Azmine Toushik Wasi and Karlo Šerbetar and Raima Islam and Taki Hasan Rafi and Dong-Kyu Chae},
      year={2023},
      eprint={2305.01486},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

References

POSTER_V2
ViT