- We update the code for Adaptive Aggregation Networks (accepted to CVPR 2021), which achieve SOTA performance on class-incremental learning tasks. Detailed comments are added for most of the functions and classes.
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Adaptive Aggregation Networks for Class-Incremental Learning, CVPR 2021. [PDF] [Project]
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Mnemonics Training: Multi-Class Incremental Learning without Forgetting, CVPR 2020. [PDF] [Project]
Please cite our paper if it is helpful to your work:
@inproceedings{Liu2020AANets,
author = {Liu, Yaoyao an 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)},
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}
}
Our implementation uses the source code from the following repositories: