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O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks

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o-gan

O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks

Requirement

Python 2.7 + Tensorflow 1.8 + Keras 2.2.4

Results

  • CelebA HQ
    CelebA HQ线性插值.jpg

  • FFHQ
    FFHQ线性插值.jpg

  • LSUN-church
    LSUN-church线性插值.jpg

  • LSUN-bedroom
    LSUN-bedroom线性插值.jpg

Reference

Cite

 @article{su2019gan,
  title={O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks},
  author={Su, Jianlin},
  journal={arXiv preprint arXiv:1903.01931},
  year={2019}
}

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O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks

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