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EBGAN

A tensorflow implementation of Junbo et al's Energy-based generative adversarial network ( EBGAN ) paper. ( See : https://arxiv.org/pdf/1609.03126v2.pdf ) My implementation is somewhat different from original papers, for example I've used convolution layers in both generator and discriminator instead of fully connected layers. I think this isn't important and will not make a big difference in the final result.

Version

Current Version : 0.0.0.2

Dependencies ( VERSION MUST BE MATCHED EXACTLY! )

  1. tensorflow == 1.0.0
  2. sugartensor == 1.0.0.2

Training the network

Execute

<pre><code> python mnist_ebgan_train.py </code></pre>

to train the network. You can see the result ckpt files and log files in the 'asset/train' directory. Launch tensorboard --logdir asset/train/log to monitor training process.

Generating image

Execute

<pre><code> python mnist_ebgan_generate.py </code></pre>

to generate sample image. The 'sample.png' file will be generated in the 'asset/train' directory.

Generated image sample

This image was generated by EBGAN network.

<p align="center"> <img src="https://raw.githubusercontent.com/buriburisuri/ebgan/master/png/sample.png" width="1024"/> </p>

Other resources

  1. Original GAN tensorflow implementation
  2. InfoGAN tensorflow implementation
  3. Supervised InfoGAN tensorflow implementation

Authors

Namju Kim (buriburisuri@gmail.com) at Jamonglabs Co., Ltd.