If you find our work inspiring or use our codebase in your research, please consider giving a star ⭐ and a citation.
@inproceedings{wan2024unlocking,
title={Unlocking the Power of Open Set: A New Perspective for Open-Set Noisy Label Learning},
author={Wan, Wenhai and Wang, Xinrui and Xie, Ming-Kun and Li, Shao-Yuan and Huang, Sheng-Jun and Chen, Songcan},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={38},
number={14},
pages={15438--15446},
year={2024}
}
- Before training with CECL, initialize training using Promix[https://github.com/Justherozen/ProMix]. Place the obtained correction records and labels into the res_stage1 folder. Then, run:
sh run.sh
- This is a demo under the cifar80N sym20% setting. You can directly use
sh run.sh
to start training. If you want to customize the training, please go to theconfig
folder and modify the relevant parameters.
- To install requirements:
pip install -r requirements.txt
- Run in linux (may have some problems in windows)