Code release for "Gradually Vanishing Bridge for Adversarial Domain Adaptation" (CVPR 2020)
Office-31 dataset can be found here.
Office-Home dataset can be found here.
VisDA 2017 dataset can be found here in the classification track.
The code is implemented with Python(3.6) and Pytorch(1.0.0).
To install the required python packages, run
pip install -r requirements.txt
Training instructions for GVB-GD and CDAN-GD are in the README.md in GVB-GD and CDAN-GD respectively.
If you use this code for your research, please consider citing:
@inproceedings{cui2020gvb,
title={Gradually Vanishing Bridge for Adversarial Domain Adaptation},
author={Cui, Shuhao and Wang, Shuhui and Zhuo, Junbao and Su, Chi and Huang, Qingming and Tian Qi},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
year={2020}
}
If you have any problem about our code, feel free to contact
or describe your problem in Issues.