Gaussian-guided feature alignment for unsupervised cross-subject adaptation

This is the implementation of Gaussian-guided feature alignment for unsupervised cross-subject adaptation in Pytorch.

Getting Started

Installation

pip install -r requirements.txt

Download dataset

Download the dataset and checkpoint from the link below and put the zip file under the current filefolder:

https://alumniubcca-my.sharepoint.com/:u:/g/personal/kuangen_zhang_alumni_ubc_ca/EVOszfZcnMJKr4M-MNap5WABiAmMPMcABCG85FQ89Pa-AQ?e=0idLuC

Test

python code/main.py

Train

python code/main.py --eval_only False

Contact

For more related works and codes, please view my homepage: https://sites.google.com/view/kuangenzhang

Further information please contact Kuangen Zhang (kuangen.zhang@alumni.ubc.ca).

Citation

If you find our work useful in your research, please consider citing:

@article{zhang_gaussian-guided_2022,
	title = {Gaussian-guided feature alignment for unsupervised cross-subject adaptation},
	volume = {122},
	issn = {0031-3203},
	language = {en},
	urldate = {2021-10-18},
	journal = {Pattern Recognition},
	author = {Zhang, Kuangen and Chen, Jiahong and Wang, Jing and Leng, Yuquan and de Silva, Clarence W. and Fu, Chenglong},
	month = feb,
	year = {2022},
	pages = {108332},
}