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PyTorch implementation of our CVPR2023 paper "OpenMix: Exploring Out-of-Distribution samples for Misclassification Detection"

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OpenMix

PyTorch implementation of our CVPR2023 paper "OpenMix: Exploring Out-of-Distribution samples for Misclassification Detection"

Usage

We run the code with torch version: 1.10.0, python version: 3.9.7

python main_cvpr.py

The outlier data can be downloaded at https://people.eecs.berkeley.edu/~hendrycks/300K_random_images.npy

Citation

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

@inproceedings{zhu2023openmix,
  title={OpenMix: Exploring Outlier Samples for Misclassification Detection},
  author={Zhu, Fei and Cheng, Zhen and Zhang, Xu-Yao and Liu, Cheng-Lin},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={12074--12083},
  year={2023}
}

Useful links

A list of papers that studies out-of-distribution (OOD) detection and misclassification detection (MisD)

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PyTorch implementation of our CVPR2023 paper "OpenMix: Exploring Out-of-Distribution samples for Misclassification Detection"

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