UJDA

Unsupervised domain adaptation with unified joint distribution alignment paper link

Prerequisites:

• Python3
• PyTorch ==0.4.1 (with suitable CUDA and CuDNN version)
• torchvision == 0.2.0
• Numpy
• tqdm

Dataset:

You need to modify the path of the image in every ".txt" in "./data".

Training:

run :

python train.py --config ../config/dann.yml   --dataset Office-31   --src_address ../data/amazon.txt    --tgt_address     ../data/dslr.txt  --src_test_address ../data/amazon.txt

Citation:

If you use this code for your research, please consider citing:

Contact

If you have any problem about our code, feel free to contact yaoyueduzhen@outlook.com.