This is the official implementation of:

Zeyi Huang, Haohan Wang, Eric P. Xing, and Dong Huang, Self-Challenging Improves Cross-Domain Generalization, ECCV, 2020 (Oral), arxiv version.

@inproceedings{huangRSC2020,
  title={Self-Challenging Improves Cross-Domain Generalization},
  author={Zeyi Huang and Haohan Wang and Eric P. Xing and Dong Huang},
  booktitle={ECCV},
  year={2020}
}

• Python ==3.7
• Pytorch >=1.0.0
• Torchvision >= 0.2.0
• Cuda >=10.0
• Tensorflow >=1.14
• GPU: RTX 2080

Download PACS dataset from here. Once you have download the data, you must update the files in data/txt_list to match the actual location of your files.

Experiments with different source/target domains are listed in train.py(L140-147). To train a ResNet18, simply run:

  python train.py

New ImageNet ResNet baselines training by RSC.

We borrowed some code and data augmentation techniques from Jigen.