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PASS - Official PyTorch Implementation

[CVPR2021 Oral] Prototype Augmentation and Self-Supervision for Incremental Learning

Fei Zhu, Xu-Yao Zhang, Chuang Wang, Fei Yin, Cheng-Lin Liu
Paper

Usage

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

  • Train CIFAR100
python main.py
  • Train Tiny-ImageNet
cd Tiny-ImageNet
python main_tiny.py
  • Train ImageNet-Subset
cd ImageNet-Subset
python main_PASS_imagenet.py

Citation

@InProceedings{Zhu_2021_CVPR,
    author    = {Zhu, Fei and Zhang, Xu-Yao and Wang, Chuang and Yin, Fei and Liu, Cheng-Lin},
    title     = {Prototype Augmentation and Self-Supervision for Incremental Learning},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2021},
    pages     = {5871-5880}
}

Reference

Our implementation references the codes in the following repositories:

Contact

Fei Zhu (zhufei2018@ia.ac.cn)

About

PyTorch implementation of our CVPR2021 (oral) paper "Prototype Augmentation and Self-Supervision for Incremental Learning"

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