Awesome

Universal Domain Adaptation

Code release for Universal Domain Adaptation(CVPR 2019)

Note

As the focus of my research has moved away from domain adaptation, this code repository may be obsolete someday. We are delighted to see that universal domain adaptation has received tremendous attention in the academic community, and readers are encouraged to discuss related questions with the authors of follow-up papers.

Requirements

python 3.6+
PyTorch 1.0

pip install -r requirements.txt

Usage

download datasets
write your config file
python main.py --config /path/to/your/config/yaml/file
train (configurations in officehome-train-config.yaml are only for officehome dataset):

python main.py --config officehome-train-config.yaml
test

python main.py --config officehome-test-config.yaml
monitor (tensorboard required)

tensorboard --logdir .

Checkpoints

We provide the checkpoints for officehome datasets at Google Drive.

Citation

please cite:

@InProceedings{UDA_2019_CVPR,
author = {You, Kaichao and Long, Mingsheng and Cao, Zhangjie and Wang, Jianmin and Jordan, Michael I.},
title = {Universal Domain Adaptation},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}