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UJDA

Unsupervised domain adaptation with unified joint distribution alignment

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.

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Unsupervised domain adaptation with unified joint distribution alignment

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