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Code release for Separate to Adapt: Open Set Domain Adaptation via Progressive Separation (CVPR 2019)

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Separate to Adapt: Open Set Domain Adaptation via Progressive Separation

(CVPR 2019) Code release for Separate to Adapt: Open Set Domain Adaptation via Progressive Separation (CVPR 2019)

Dataset

Office-31

Requirements

  • python 2.7
  • PyTorch 0.4
  • Tensorflow >= 1.0
  • Tensorlayer >= 1.11
  • Tensorboard
  • torchvision

Training

  • Download datasets
  • Step 1: python step_1.py, the known\unknown discriminator is saved as discriminator_a.pkl
  • Step 2: python step_2.py
  • Optional: iterate between step 1&2 to achieve better results
  • Monitor tensorboard --logdir .

Citation

please cite:

@InProceedings{Liu_2019_CVPR,
author = {Liu, Hong and Cao, Zhangjie and Long, Mingsheng and Wang, Jianmin and Yang, Qiang},
title = {Separate to Adapt: Open Set Domain Adaptation via Progressive Separation},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
} 

Reference codes

https://github.com/thuml/easydl

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Code release for Separate to Adapt: Open Set Domain Adaptation via Progressive Separation (CVPR 2019)

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