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Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective

Zhengzhuo Xu, Zenghao Chai, Chun Yuan


This is the PyTorch implementation of our paper in NeurIPS 2021.

Environment settings

  • PyTorch >= 1.4
  • Scikit-learn
  • Matplotlib

Training

To train the model, please select a config file path or customize by yourself. For example:

python train.py config/cifar10_100.py

The result will be saved in ./result.

Inferance model

Dataset log Model
CIFAR-10-LT-50 link link
CIFAR-10-LT-100 link link
CIFAR-10-LT-200 link link
CIFAR-100-LT-50 link link
CIFAR-100-LT-100 link link
CIFAR-100-LT-200 link link

Note

  • Some settings may be a little different from the paper reported. Because we make further optimization considering reviewers' suggestions.
  • Some bugs need to be fixed when imb factor = 0.1
  • Need to solve the test-agnostic situation.

Reference

Welcome to cite:

@inproceedings{PriorLT,
    title={Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective},
    author={Xu, Zhengzhuo and Chai, Zenghao and Yuan, Chun},
    booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
    year={2021}
}

Acknowledgement

We adopt the code from the following repos. We thank them for providing their awesome code.

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