DCGAN_WGAN_WGAN-GP_LSGAN_SNGAN_RSGAN_BEGAN_ACGAN_PGGAN_TensorFlow is being sponsored by the following tool; please help to support us by taking a look and signing up to a free trial
Implementation of some different variants of GANs
This code is mainly implement some basic GANs about 'DCGAN', 'WGAN', 'WGAN-GP', 'LSGAN', 'SNGAN', 'RSGAN'&'RaSGAN', 'BEGAN', 'ACGAN', 'PGGAN', 'pix2pix', 'BigGAN'.
More details of these GANs, please see follow papers:
DCGAN: Unsupervised representation learning with deep convolutional generative adversarial networks
WGAN: Wasserstein gan
WGAN-GP: Improved training of wasserstein gans
LSGAN: Least Squares Generative Adversarial Networks
SNGAN: Spectral normalization for generative adversarial networks
RSGAN&RaSGAN: The relativistic discriminator: a key element missing from standard GAN
BEGAN:BEGAN: Boundary Equilibrium Generative Adversarial Networks
ACGAN: Conditional Image Synthesis With Auxiliary Classifier GANs
PGGAN: Progressive Growing of GANs for Improved Quality, Stability, and Variation
pix2pix: Image-to-Image Translation with Conditional Adversarial Networks
BigGAN: Large Scale GAN Training for High Fidelity Natural Image Synthesis [Code]
If your computer don't have GPU to accelerate the training process, please click Google Cloud Colab to train the GANs.
How to use
Firstly, you should download the data 'facedata.mat' from Baidu Drive or Google Drive, then put the file 'facedata.mat' into the folder 'TrainingSet'.
Results of this code
This result is using DCGAN trained about 8000 iterations.
Compare LSGAN, WGAN, WGAN-GP, SNGAN, RSGAN of different iteration
Convergence of BEGAN
ACGAN for face generating
dataset: download address: Baidu Drive password: 5egd
|Fixed label, change noise slightly
||Fixed noise, change label slightly
PGGAN for face generating
SNGAN for cifar-10
Dataset: Google maps download address: http://efrosgans.eecs.berkeley.edu/pix2pix/datasets/maps.tar.gz
Edges2Shoes download address: http://efrosgans.eecs.berkeley.edu/pix2pix/datasets/edges2shoes.tar.gz