wangliang233/class-incremental-learning

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

Class-Incremental Learning

Papers

• Adaptive Aggregation Networks for Class-Incremental Learning, CVPR 2021. [PDF] [Project Page]

• Mnemonics Training: Multi-Class Incremental Learning without Forgetting, CVPR 2020. [PDF] [Project Page]

Citations

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

@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}
}

@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

• iCaRL: Incremental Classifier and Representation Learning

• Dataset Distillation

• Generative Teaching Networks