code release for "Heuristic Domain Adaptation"(NIPS2020)
We address the construction of domain-invariant and domain-specific representations from the heuristic search perspective.
- pytorch = 1.3.0
- torchvision = 0.4.1
- numpy = 1.17.2
- pillow = 6.2.0
- python3.7
- cuda10
To install the required python packages, run
pip install -r requirements.txt
Office-Home dataset can be found here.
Domainnet dataset can be found here.
The training of HDA could be utilized by changing the path of the dataset, such as the txt files in data/UDA_officehome/Art.txt.
Also, the txt files for SSDA and MSDA should be compressed.
cd data
unzip data.zip
bash scripts/run_uda.sh
bash scripts/run_msda.sh
bash scripts/run_ssda.sh
If you use this code for your research, please consider citing:
@inproceedings{cui2020hda,
author = {Cui, Shuhao and Jin, Xuan and Wang, Shuhui and He, Yuan and Huang, Qingming},
booktitle = {Advances in Neural Information Processing Systems},
pages = {7571--7583},
publisher = {Curran Associates, Inc.},
title = {Heuristic Domain Adaptation},
volume = {33},
year = {2020}
}
If you have any problem about our code, feel free to contact
or describe your problem in Issues.
Supplemantary could be found in google driver and baidu cloud with 8yut.