Classified Papers of GAN Applications
GAIN：MissingData Imputation using Generative Adversarial Nets [Paper] [Code]
CollaGAN : Collaborative GAN for Missing Image Data Imputation [Paper] [Code] (CVPR 2019)
Image super-resolution through deep learning [Code](Just for face dataset)
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network [Paper][Code]（SRGAN/Using Deep residual network）
EnhanceGAN [Docs][[Code]]
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks [Paper][Code](ECCV 2018 workshop)
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks [Paper][Code](Gan with convolutional networks)(ICLR)
Improved Techniques for Training GANs [Paper][Code](Goodfellow's paper)
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space [Paper][Code]
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks [Paper][Code]
Improved Training of Wasserstein GANs [Paper][Code]
Boundary Equibilibrium Generative Adversarial Networks Implementation in Tensorflow [Paper][Code]
Progressive Growing of GANs for Improved Quality, Stability, and Variation [Paper][Code][Tensorflow Code]
Self-Attention Generative Adversarial Networks [Paper][Code](NIPS 2018)
Large Scale GAN Training for High Fidelity Natural Image Synthesis [Paper](ICLR 2019)
A Style-Based Generator Architecture for Generative Adversarial Networks [Paper][Code]
Analyzing and Improving the Image Quality of StyleGAN [Paper][Code]
SinGAN: Learning a Generative Model from a Single Natural Image [Paper][Code](ICCV2019 best paper)
Real or Not Real, that is the Question [Paper][Code](ICLR2020 Spot)
Training End-to-end Single Image Generators without GANs [Paper]
Adversarial Latent Autoencoders [Paper][code]
Connecting Generative Adversarial Networks and Actor-Critic Methods [Paper](NIPS 2016 workshop)