Thi repository is for the paper "Learning a Unified Classifier Incrementally via Rebalancing".

[Paper] [Project Page]

1. Dependencies
   • Python 3.6 (Anaconda3 Recommended)
   • Pytorch 0.4.0
2. Getting Started
   • the data for CIFAR100 and ImageNet are put in cifar100-class-incremental/data and imagenet-class-incremental/data, or you can make soft links to the directories which include the corresponding data
   • see cifar100-class-incremental/run.sh for the experiments on CIFAR100
   • see imagenet-class-incremental/run.sh for the experiments on ImageNet-Subset
   • see imagenet-class-incremental/run_all.sh for the experiments on ImageNet-Full

Please cite the following paper if you find this useful in your research:

@InProceedings{Hou_2019_CVPR,
author = {Hou, Saihui and Pan, Xinyu and Loy, Chen Change and Wang, Zilei and Lin, Dahua},
title = {Learning a Unified Classifier Incrementally via Rebalancing},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}