bojone / O Gan
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
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CelebA HQ
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FFHQ
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LSUN-church
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LSUN-bedroom
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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