SymNets

Official PyTroch implementation for "Domain-Symnetric Networks for Adversarial Domain Adaptation (CVPR 2019)". A sinigficant journal extension of this work (including a novel theoretical framework) is introduced at "Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice". Codes .

Prerequisites

Linux

NVIDIA GPU + CUDA (may CuDNN) and corresponding PyTorch framework (version 0.5.0)

Python 3.6

Training and Evaluation

Please refer to 'run.sh'

Citation

@inproceedings{zhang2019domain,
  title={Domain-symmetric networks for adversarial domain adaptation},
  author={Zhang, Yabin and Tang, Hui and Jia, Kui and Tan, Mingkui},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={5031--5040},
  year={2019}
}
@article{zhang2020unsupervised,
  title={Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice},
  author={Zhang, Yabin and Deng, Bin and Tang, Hui and Zhang, Lei and Jia, Kui},
  journal={arXiv preprint arXiv:2002.08681},
  year={2020}
}

Contact

If you have any problem about our code, feel free to contact

• zhang.yabin@mail.scut.edu.cn

or describe your problem in Issues.