Awesome-GANs with Tensorflow

Tensorflow implementation of GANs(Generative Adversarial Networks)

Prerequisites

python 3.5+
tensorflow 1.1.0+
scipy
pillow
h5py
pickle
glob, tqdm
(sklearn for train_test_split)

Usage

(before running train.py, make sure run after downloading dataset & changing dataset directory in train.py)
just download it and run train.py
$ python3 train.py

Datasets

Now supporting(?) DataSets are... (code is in /datasets.py)

MNIST
Cifar-10
Cifar-100
Celeb-A
pix2pix shoes
pix2pix bags
(more DataSets will be added soon!)

Papers & Codes

ACGAN : Auxiliary Classifier Generative Adversarial Networks [arXiv]
AdaGAN : Boosting Generative Models [arXiv]
BEGAN : Boundary Equilibrium Generative Adversarial Networks [arXiv] [code]
BSGAN : Boundary-Seeking Generative Adversarial Networks [arXiv]
CGAN : Conditional Generative Adversarial Networks [arXiv] [code]
CoGAN : Coupled Generative Adversarial Networks [arXiv]
DCGAN : Deep Convolutional Generative Adversarial Networks [arXiv] [code]
DiscoGAN : Discover Cross-Domain Generative Adversarial Networks [arXiv] [code]
EnergyGAN : Energy-based Generative Adversarial Networks [arXiv]
f-GAN : Training Generative Neural Samplers using Variational Divergence Minimization [arXiv]
GAN : Generative Adversarial Networks [arXiv] [code]
Softmax GAN : Generative Adversarial Networks with Softmax [arXiv] [code]
GAP : Generative Adversarial Parallelization [arXiv]
InfoGAN : Interpretable Representation Learning by Information Maximizing Generative Adversarial Networks [arXiv]
LAPGAN : Laplacian Pyramid Generative Adversarial Networks [arXiv]
LSGAN : Loss-Sensitive Generative Adversarial Networks [arXiv]
MAGAN : Margin Adaptation for Generative Adversarial Networks [arXiv]
MRGAN : Mode Regularized Generative Adversarial Networks [arXiv]
SalGAN : Visual Saliency Prediction Generative Adversarial Networks [arXiv]
SeqGAN : Sequence Generative Adversarial Networks with Policy Gradient [arXiv]
SGAN : Stacked Generative Adversarial Networks [arXiv]
WGAN : Wasserstein Generative Adversarial Networks [arXiv]
ImprovedWGAN : Improved Training of Wasserstein Generative Adversarial Networks [arXiv]