Counterfactual Attention Learning

Created by Yongming Rao*, Guangyi Chen*, Jiwen Lu, Jie Zhou

This repository contains PyTorch implementation for ICCV 2021 paper Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification [arXiv]

We propose to learn the attention with counterfactual causality, which provides a tool to measure the attention quality and a powerful supervisory signal to guide the learning process.

CAL for Fine-Grained Visual Categorization

See CAL-FGVC.

CAL for Person Re-Identification

See CAL-ReID.

License

MIT License

Citation

If you find our work useful in your research, please consider citing:

@inproceedings{rao2021counterfactual,
  title={Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification},
  author={Rao, Yongming and Chen, Guangyi and Lu, Jiwen and Zhou, Jie},
  booktitle={ICCV},
  year={2021}
}