Skip to content

Code release for "Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice"

License

Notifications You must be signed in to change notification settings

TANG16/MultiClassDA

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

MultiClassDA

Code release for "Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice", which is an extension of our preliminary work of SymmNets [Paper] [Code]

Code to be updated:

  1. Code of McDalNets
    1. For the Office-31, ImageCLEF, Office-Home, VisDA-2017 datasets (Finished)
    2. For the Digits dataset
  2. Code of SymNets-V2
    1. For the Closed Set DA
      1. Based on the ResNet (Finished)
      2. Based on the AlexNet
      3. For the Digits dataset
      4. Strengthened for Closed Set UDA
    2. For the Partial DA
      1. Based on the ResNet
      2. Based on the AlexNet
    3. For the Open Set DA
      1. Based on the ResNet

Dataset

To be updated.

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}
}

Contact

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

or describe your problem in Issues.

About

Code release for "Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice"

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 97.7%
  • Shell 2.3%