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Awesome-GANs

Awesome Generative Adversarial Networks with tensorflow

Awesome-GANs with Tensorflow

Tensorflow implementation of GANs (Generative Adversarial Networks)

WIP : This repo is about to be refactored & supporting `tf 2.x`.

Maybe some codes wouldn’t work on master branch, because i’m just working on the branch.

Environments

Because of the image and model size, (especially BEGAN, SRGAN, StarGAN, … using high resolution images as input), if you want to train them comfortably, you need a GPU which has more than 8GB.

But, of course, the most of the implementations use MNIST or CIFAR-10, 100 DataSets. Meaning that we can handle it with EVEN lower spec GPU than ‘The Preferred’ :).

Usage

Now on refactoring… All GAN training script can be run module-wisely like below. (WIP)

Install dependencies

You can also use conda, virtualenv environments.

```shell script $ python3 -m pip install -r requirements.txt

### Train GANs

Before running the model, make sure that 

1. downloading the dataset like *CelebA*, *MNIST*, etc what you want
2. In `awesome_gans/config.py`, there are several configurations, customize with your flavor!
3. running the model like below

```shell script
$ python3 -m awesome_gans.acgan

DataSets

Supporting datasets are … (code is in /awesome_gans/datasets.py)

MNIST / ~~Fashion MNIST~~
CIFAR10 / 100
CelebA/CelebA-HQ
Pix2Pix
DIV2K
(more DataSets will be added soon!)

Repo Tree

│
├── awesome_gans (source codes & eplainations & results & models) 
│        │
│        ├── acgan
│        │    ├──gen_img (generated images)
│        │    │     ├── train_xxx.png
│        │    │     └── train_xxx.png
│        │    ├── model  (pre-trained model file)
│        │    │     └── model.txt (google-drive link)
│        │    ├── __init__.py
│        │    ├── __main__.py
│        │    ├── model.py (gan model)
│        │    ├── train.py (gan trainer)
│        │    ├── gan_tb.png   (tensorboard loss plot)
│        │    └── readme.md    (results & explainations)
│        ├── config.py         (configurations)
│        ├── modules.py        (networks & operations)
│        ├── utils.py          (auxiliary utils)
│        ├── image_utils.py    (image processing)
│        └── datasets.py       (dataset loader)
├── CONTRIBUTING.md
├── Makefile   (for linting the codes)
├── LICENSE
├── README.md  (Usage & GAN paper list-up)
└── requirements.txt

Papers & Codes

Here’s the list-up for tons of GAN papers. all papers are sorted by alphabetic order.

Start

Here’s the beginning of the GAN.

Name	Summary	Paper	Code
GAN	Generative Adversarial Networks	[arXiv]	[code]

Theory & Concept

Here for the theories & concepts of the GAN.

Name	Summary	Paper	Code	Official Code
ACGAN	Auxiliary Classifier Generative Adversarial Networks	[arXiv]	[code]
AdaGAN	Boosting Generative Models	[arXiv]	[~~code~~]
bCR	Improved Consistency Regularization for GANs	[arXiv]	[~~code~~]
BEGAN	Boundary Equilibrium Generative Adversarial Networks	[arXiv]	[code]
BGAN	Boundary-Seeking Generative Adversarial Networks	[arXiv]	[code]
BigGAN	Large Scale GAN Training for High Fidelity Natural Image Synthesis	[arXiv]	[~~code~~]
CGAN	Conditional Generative Adversarial Networks	[arXiv]	[code]
CoGAN	Coupled Generative Adversarial Networks	[arXiv]	[code]
ConSinGAN	Improved Techniques for Training Single-Image GANs	[WACV21]	[~~code~~]	[official]
DCGAN	Deep Convolutional Generative Adversarial Networks	[arXiv]	[code]
DRAGAN	On Convergence and Stability of Generative Adversarial Networks	[arXiv]	[code]
EBGAN	Energy-based Generative Adversarial Networks	[arXiv]	[code]
EqGAN-SA	Improving GAN Equilibrium by Raising Spatial Awareness	[arXiv]	[~~code~~]	[official]
f-GAN	Training Generative Neural Samplers using Variational Divergence Minimization	[arXiv]	[code]
GP-GAN	Towards Realistic High-Resolution Image Blending	[arXiv]	[~~code~~]
Softmax GAN	Generative Adversarial Networks with Softmax	[arXiv]	[code]
GAP	Generative Adversarial Parallelization	[arXiv]	[~~code~~]
GEGAN	Generalization and Equilibrium in Generative Adversarial Networks	[arXiv]	[~~code~~]
G-GAN	Geometric GAN	[arXiv]	[~~code~~]
InfoGAN	Interpretable Representation Learning by Information Maximizing Generative Adversarial Networks	[arXiv]	[code]
LAPGAN	Laplacian Pyramid Generative Adversarial Networks	[arXiv]	[code]
LSGAN	Loss-Sensitive Generative Adversarial Networks	[arXiv]	[code]
MAGAN	Margin Adaptation for Generative Adversarial Networks	[arXiv]	[code]
MRGAN	Mode Regularized Generative Adversarial Networks	[arXiv]	[code]
MSGGAN	Multi-Scale Gradients for Generative Adversarial Networks	[arXiv]	[~~code~~]
PGGAN	Progressive Growing of GANs for Improved Quality, Stability, and Variation	[arXiv]	[~~code~~]	[official]
RaGAN	The relativistic discriminator: a key element missing from standard GAN	[arXiv]	[~~code~~]
SeAtGAN	Self-Attention Generative Adversarial Networks	[arXiv]	[code]
SphereGAN	Sphere Generative Adversarial Network Based on Geometric Moment Matching	[CVPR2019]	[~~code~~]
SGAN	Stacked Generative Adversarial Networks	[arXiv]	[~~code~~]
SGAN++	Realistic Image Synthesis with Stacked Generative Adversarial Networks	[arXiv]	[~~code~~]
SinGAN	Learning a Generative Model from a Single Natural Image	[arXiv]	[~~code~~]	[official]
StableGAN	Stabilizing Adversarial Nets With Prediction Methods	[arXiv]	[~~code~~]
StyleCLIP	Text-Driven Manipulation of StyleGAN Imagery	[arXiv]	[~~code~~]	[official]
StyleGAN	A Style-Based Generator Architecture for Generative Adversarial Networks	[arXiv]	[~~code~~]	[official]
StyleGAN2	Analyzing and Improving the Image Quality of StyleGAN	[arXiv]	[~~code~~]	[official]
StyleGAN2 ADA	StyleGAN2 with adaptive discriminator augmentation	[arXiv]	[~~code~~]	[official]
StyleGAN3	Alias-Free Generative Adversarial Networks	[arXiv]	[~~code~~]	[official]
StyleGAN-XL	Scaling StyleGAN to Large Diverse Datasets	[arXiv]	[~~code~~]	[official]
TripleGAN	Triple Generative Adversarial Networks	[arXiv]	[~~code~~]
UGAN	Unrolled Generative Adversarial Networks	[arXiv]	[~~code~~]
U-Net GAN	A U-Net Based Discriminator for Generative Adversarial Networks	[CVPR20]	[~~code~~]	[official]
WGAN	Wasserstein Generative Adversarial Networks	[arXiv]	[code]
WGAN-GP	Improved Training of Wasserstein Generative Adversarial Networks	[arXiv]	[code]

Applied Vision

Here for the GAN applications on Vision domain, like image-to-image translation, image in-painting, single image super resolution , etc.

Name	Summary	Paper	Code	Official Code
3D GAN	3D Generative Adversarial Networks	[MIT]	[~~code~~]
AnycostGAN	Anycost GANs for Interactive Image Synthesis and Editing	[arXiv]	[~~code~~]	[official]
CycleGAN	Unpaired img2img translation using Cycle-consistent Adversarial Networks	[arXiv]	[code]
DAGAN	Instance-level Image Translation by Deep Attention Generative Adversarial Networks	[arXiv]	[~~code~~]
DeblurGAN	Blind Motion Deblurring Using Conditional Adversarial Networks	[arXiv]	[~~code~~]
DualGAN	Unsupervised Dual Learning for Image-to-Image Translation	[arXiv]	[~~code~~]
DRIT/++	Diverse Image-to-Image Translation via Disentangled Representations	[arXiv]	[~~code~~]	[official]
EdgeConnect	Generative Image Inpainting with Adversarial Edge Learning	[arXiv]	[~~code~~]	[official]
ESRGAN	Enhanced Super-Resolution Generative Adversarial Networks	[arXiv]	[~~code~~]
FastGAN	Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis	[arXiv]	[~~code~~]	[official]
FUNIT	Few-Shot Unsupervised Image-to-Image Translation	[arXiv]	[~~code~~]	[official]
CA & GA	Generative Image Inpainting w/ Contextual Attention & Gated Convolution	[CVPR2018], [ICCV2019]	[~~code~~]	[official]
HiFaceGAN	Face Renovation via Collaborative Suppression and Replenishment	[arXiv]	[~~code~~]
MUNIT	Multimodal Unsupervised Image-to-Image Translation	[arXiv]	[~~code~~]	[official]
NICE-GAN	Reusing Discriminators for Encoding	[arXiv]	[~~code~~]	[official]
PSGAN	Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer	[arXiv]	[~~code~~]	[official]
SpAtGAN	Generative Adversarial Network with Spatial Attention for Face Attribute Editing	[ECCV2018]	[~~code~~]
SalGAN	Visual Saliency Prediction Generative Adversarial Networks	[arXiv]	[~~code~~]
SRFlow	Super-Resolution using Normalizing Flow	[arXiv]	[~~code~~]	[official]
SRGAN	Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network	[arXiv]	[code]
SRResCGAN	Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution	[arXiv]	[~~code~~]	[official]
StarGAN	Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation	[arXiv]	[code]	[official]
StarGAN V2	Diverse Image Synthesis for Multiple Domains	[arXiv]	[~~code~~]	[official]
StyleGAN-V	A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2	[arXiv]	[~~code~~]	[official]
TecoGAN	Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation	[arXiv]	[~~code~~]	[official]
TextureGAN	Controlling Deep Image Synthesis with Texture Patches	[arXiv]	[~~code~~]
TUNIT	Rethinking the Truly Unsupervised Image-to-Image Translation	[arXiv]	[~~code~~]	[official]
TwinGAN	Cross-Domain Translation fo Human Portraits	[github]	[~~code~~]
UNIT	Unsupervised Image-to-Image Translation Networks	[arXiv]	[~~code~~]	[official]
XGAN	Unsupervised Image-to-Image Translation for Many-to-Many Mappings	[arXiv]	[~~code~~]
Zero-DCE	Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement	[CVPR20]	[~~code~~]	[official]

Applied Audio

Here for the GAN applications on Audio domain, like wave generation, wave to wave translation, etc.

Name	Summary	Paper	Code
AAS	Adversarial Audio Synthesis	[arXiv]	[~~code~~]
BeatGAN	Generating Drum Loops via GANs	[arXiv]	[~~code~~]
GANSynth	Adversarial Neural Audio Synthesis	[arXiv]	[~~code~~]
MuseGAN	Multi-track Sequential GANs for Symbolic Music Generation and Accompaniment	[arXiv]	[~~code~~]
SEGAN	Speech Enhancement Generative Adversarial Network	[arXiv]	[~~code~~]
StarGAN-VC	Non-parallel many-to-many voice conversion with star generative adversarial networks	[arXiv]	[~~code~~]
TempoGAN	A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow	[arXiv]	[~~code~~]
Parallel WaveGAN	A fast waveform generation model based on GAN with multi-resolution spectrogram	[arXiv]	[~~code~~]
WaveGAN	Synthesizing Audio with Generative Adversarial Networks	[arXiv]	[~~code~~]

Applied Others

Here for the GAN applications on other domains, like nlp, tabular, etc.

Name	Summary	Paper	Code
AnoGAN	Unsupervised Anomaly Detection with Generative Adversarial Networks	[arXiv]	[~~code~~]
CipherGAN	Unsupervised Cipher Cracking Using Discrete GANs	[github]	[~~code~~]
DiscoGAN	Discover Cross-Domain Generative Adversarial Networks	[arXiv]	[~~code~~]
eCommerceGAN	A Generative Adversarial Network for E-commerce	[arXiv]	[~~code~~]
PassGAN	A Deep Learning Approach for Password Guessing	[arXiv]	[~~code~~]
SeqGAN	Sequence Generative Adversarial Networks with Policy Gradient	[arXiv]	[~~code~~]
TAC-GAN	Text Conditioned Auxiliary Classifier Generative Adversarial Network	[arXiv]	[~~code~~]

Useful Resources

Here for the useful resources when you try to train and stable a gan model.

Name	Summary	Link
GAN Hacks	a bunch of tips & tricks to train GAN stable	github

Note

Any suggestions and PRs and issues are WELCOME :)

Author

HyeongChan Kim / @kozistr