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PyTorch implementation for Prototype-Based Multisource Domain Adaptation (TNNLS2021). This repository is based on framework from dassl and modified part of the code.

The installation can refer to dassl.

Please download dig-5, office-31, office-home to datasets folder.

Training:

CUDA_VISIBLE_DEVICES=1 python tools/train.py --trainer MSDTR_CDAN --source-domains mnist mnist_m svhn syn --target-domains usps  --dataset-config-file configs/datasets/digit5.yaml --config-file configs/trainers/msdtr_cdan/digit5.yaml --output-dir output_final/msdtr_cdan/dig/usps/1

Citation

If you use this code for your research, please cite our paper:

@article{zhou2021prototype,
  title={Prototype-Based Multisource Domain Adaptation},
  author={Zhou, Lihua and Ye, Mao and Zhang, Dan and Zhu, Ce and Ji, Luping},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2021},
  publisher={IEEE}
}