This repo is the official implementation of DER: Dynamically Expandable Representation for Class Incremental Learning (CVPR 2021)
- ImageNet100 Refer to ImageNet100_Split
- Change to corresponding directory and run the following commands
sh scripts/run.sh
Inference command:
sh scripts/inference.sh
- create a new exp folder
rsync -rv --exclude=tensorboard --exclude=logs --exclude=ckpts --exclude=__pycache__ --exclude=results --exclude=inbox ./codes/base/ ./exps/der_womask/10steps/trial0
Thanks for the great code base from https://github.com/arthurdouillard/incremental_learning.pytorch.
If you are using the DER in your research or with to refer to the baseline results published in this repo, please use the following BibTex entry.
@article{yan2021dynamically,
title={DER: Dynamically Expandable Representation for Class Incremental Learning},
author={Yan, Shipeng and Xie, Jiangwei and He, Xuming},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2021}
}