Official PyTorch implementation of "Cross-Domain Ensemble Distillation for Domain Generalization" (ECCV 2022)
For more information, please checkout our website and paper.
conda env create --file environment.yaml
conda activate xded
python pacs_cartoon_train.py --gpu-id 0 --IPC 16 \
--dataset-config-file configs/datasets/domain_ipc_pacs.yaml \
--config-file configs/xded_default.yaml \
--trainer XDED --remark XDED_UniStyle12 \
MODEL.BACKBONE.NAME resnet18_UniStyle_12
Our code is based on Dassl.pytorch. We thank Kaiyang Zhou for this great repository.
In case of using this source code for your research, please cite our paper.
@inproceedings{lee2022cross,
title={Cross-Domain Ensemble Distillation for Domain Generalization},
author={Lee, Kyungmoon and Kim, Sungyeon and Kwak, Suha},
booktitle={Proceedings of European Conference on Computer Vision (ECCV)},
year={2022}
}