https://github.com/yaoyao-liu/class-incremental-learning

PyTorch implementation of AANets (CVPR 2021) and Mnemonics Training (CVPR 2020 Oral)
https://github.com/yaoyao-liu/class-incremental-learning

class-incremental-learning continual-learning

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PyTorch implementation of AANets (CVPR 2021) and Mnemonics Training (CVPR 2020 Oral)

• Host: GitHub
• URL: https://github.com/yaoyao-liu/class-incremental-learning
• Owner: yaoyao-liu
• License: mit
• Created: 2020-02-24T11:55:22.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2022-12-29T18:16:37.000Z (over 1 year ago)
• Last Synced: 2024-04-20T17:00:38.591Z (5 months ago)
• Topics: class-incremental-learning, continual-learning
• Language: Python
• Homepage: https://class-il.mpi-inf.mpg.de
• Size: 106 KB
• Stars: 453
• Watchers: 13
• Forks: 69
• Open Issues: 28
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Class-Incremental Learning

[![LICENSE](https://img.shields.io/badge/license-MIT-green?style=flat-square)](https://github.com/yaoyao-liu/class-incremental-learning/blob/master/LICENSE)

[![Python](https://img.shields.io/badge/python-3.6-blue.svg?style=flat-square&logo=python&color=3776AB&logoColor=3776AB)](https://www.python.org/)

[![PyTorch](https://img.shields.io/badge/pytorch-1.2.0-%237732a8?style=flat-square&logo=PyTorch&color=EE4C2C)](https://pytorch.org/)

### Papers

- Adaptive Aggregation Networks for Class-Incremental Learning,

CVPR 2021. \[[PDF](https://openaccess.thecvf.com/content/CVPR2021/papers/Liu_Adaptive_Aggregation_Networks_for_Class-Incremental_Learning_CVPR_2021_paper.pdf)\] \[[Project Page](https://class-il.mpi-inf.mpg.de/)\]

- Mnemonics Training: Multi-Class Incremental Learning without Forgetting,

CVPR 2020. \[[PDF](https://arxiv.org/pdf/2002.10211.pdf)\] \[[Project Page](https://class-il.mpi-inf.mpg.de/mnemonics-training/)\]

### Citations

Please cite our papers if they are helpful to your work:

```bibtex

@inproceedings{Liu2020AANets,

  author    = {Liu, Yaoyao and Schiele, Bernt and Sun, Qianru},

  title     = {Adaptive Aggregation Networks for Class-Incremental Learning},

  booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},

  pages     = {2544-2553},

  year      = {2021}

}

```

```bibtex

@inproceedings{liu2020mnemonics,

author    = {Liu, Yaoyao and Su, Yuting and Liu, An{-}An and Schiele, Bernt and Sun, Qianru},

title     = {Mnemonics Training: Multi-Class Incremental Learning without Forgetting},

booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},

pages     = {12245--12254},

year      = {2020}

}

```

### Acknowledgements

Our implementation uses the source code from the following repositories:

* [Learning a Unified Classifier Incrementally via Rebalancing](https://github.com/hshustc/CVPR19_Incremental_Learning)

* [iCaRL: Incremental Classifier and Representation Learning](https://github.com/srebuffi/iCaRL)

* [Dataset Distillation](https://github.com/SsnL/dataset-distillation)

* [Generative Teaching Networks](https://github.com/uber-research/GTN)