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.
Current Version : 0.0.0.2
- tensorflow == 1.0.0
- sugartensor == 1.0.0.2
Execute
python mnist_ebgan_train.py
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.
Execute
python mnist_ebgan_generate.py
to generate sample image. The 'sample.png' file will be generated in the 'asset/train' directory.
This image was generated by EBGAN network.
- Original GAN tensorflow implementation
- InfoGAN tensorflow implementation
- Supervised InfoGAN tensorflow implementation
Namju Kim (buriburisuri@gmail.com) at Jamonglabs Co., Ltd.