zhouzhaorun / DCGAN_WGAN_WGAN-GP_LSGAN_SNGAN_RSGAN_RaSGAN_TensorFlow

Implementation of some different variants of GANs by tensorflow, DCGAN, WGAN, WGAN-GP, LSGAN, SNGAN, RSGAN, RaSGAN

DCGAN_LSGAN_WGAN_WGAN-GP_SNGAN_RSGAN_RaSGAN

Implementation of some different variants of GANs

Introduction

This code is mainly implement some basic GANs about 'DCGAN', 'WGAN', 'WGAN-GP', 'LSGAN', 'SNGAN', 'RSGAN'&'RaSGAN'.

More details of these GANs, please see follow papers:

1. DCGAN: Unsupervised representation learning with deep convolutional generative adversarial networks

2. WGAN: Wasserstein gan

3. WGAN-GP: Improved training of wasserstein gans

4. LSGAN: Least Squares Generative Adversarial Networks

5. SNGAN: Spectral normalization for generative adversarial networks

6. RSGAN&RaSGAN: The relativistic discriminator: a key element missing from standard GAN

How to use

Firstly, you should download the data 'facedata.mat' from BaiduYun, then put the file 'facedata.mat' into the folder 'TrainingSet'.

Necessory python packages are as follow:

1. tensorflow

2. pillow

3. scipy

4. numpy

Results of this code

This result is using DCGAN trained about 8000 iterations.

Compare LSGAN, WGAN, WGAN-GP, SNGAN, RSGAN of different iteration