The classic about Generative Adversarial Networks

First paper

heavy_check_mark [Generative Adversarial Nets] [Paper] [Code](the First paper of GAN)


heavy_check_mark [Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks] [Paper][Code]

heavy_check_mark [Adversarial Autoencoders] [Paper][Code]

heavy_check_mark [Generating Images with Perceptual Similarity Metrics based on Deep Networks] [Paper]

heavy_check_mark [Generating images with recurrent adversarial networks] [Paper][Code]

heavy_check_mark [Generative Visual Manipulation on the Natural Image Manifold] [Paper][Code]

heavy_check_mark [Learning What and Where to Draw] [Paper][Code]

heavy_check_mark [Adversarial Training for Sketch Retrieval] [Paper]

heavy_check_mark [Generative Image Modeling using Style and Structure Adversarial Networks] [Paper][Code]

heavy_check_mark [Generative Adversarial Networks as Variational Training of Energy Based Models] [Paper](ICLR 2017)

heavy_check_mark [Synthesizing the preferred inputs for neurons in neural networks via deep generator networks] [Paper][Code]

heavy_check_mark [SalGAN: Visual Saliency Prediction with Generative Adversarial Networks] [Paper][Code]

heavy_check_mark [Adversarial Feature Learning] [Paper]

heavy_check_mark [Adversarially Learned Inference][Paper][Code]

GAN Theory

heavy_check_mark [Energy-based generative adversarial network] [Paper][Code](Lecun paper)

heavy_check_mark [Improved Techniques for Training GANs] [Paper][Code](Goodfellow's paper)

heavy_check_mark [Mode Regularized Generative Adversarial Networks] [Paper](Yoshua Bengio , ICLR 2017)

heavy_check_mark [Improving Generative Adversarial Networks with Denoising Feature Matching] [Paper][Code](Yoshua Bengio , ICLR 2017)

heavy_check_mark [Sampling Generative Networks] [Paper][Code]

heavy_check_mark [How to train Gans] [Docu]

heavy_check_mark [Towards Principled Methods for Training Generative Adversarial Networks] [Paper](ICLR 2017)

heavy_check_mark [Unrolled Generative Adversarial Networks] [Paper][Code](ICLR 2017)

heavy_check_mark [Least Squares Generative Adversarial Networks] [Paper][Code](ICCV 2017)

heavy_check_mark [Wasserstein GAN] [Paper][Code]

heavy_check_mark [Improved Training of Wasserstein GANs] [Paper][Code](The improve of wgan)

heavy_check_mark [Towards Principled Methods for Training Generative Adversarial Networks] [Paper]

heavy_check_mark [Generalization and Equilibrium in Generative Adversarial Nets] [Paper](ICML 2017)

heavy_check_mark [GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium][Paper][code]

heavy_check_mark [Spectral Normalization for Generative Adversarial Networks][Paper][code](ICLR 2018)

heavy_check_mark [Which Training Methods for GANs do actually Converge][Paper][code](ICML 2018)

Generation High-Quality Images

heavy_check_mark [Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks] [Paper][Code](Gan with convolutional networks)(ICLR)

heavy_check_mark [Generative Adversarial Text to Image Synthesis] [Paper][Code][code]

heavy_check_mark [Improved Techniques for Training GANs] [Paper][Code](Goodfellow's paper)

heavy_check_mark [Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space] [Paper][Code]

heavy_check_mark [StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks] [Paper][Code]

heavy_check_mark [Improved Training of Wasserstein GANs] [Paper][Code]

heavy_check_mark [Boundary Equibilibrium Generative Adversarial Networks Implementation in Tensorflow] [Paper][Code]

heavy_check_mark [Progressive Growing of GANs for Improved Quality, Stability, and Variation] [Paper][Code][Tensorflow Code]

heavy_check_mark [ Self-Attention Generative Adversarial Networks ] [Paper][Code]

Semi-supervised learning

heavy_check_mark [Adversarial Training Methods for Semi-Supervised Text Classification] [Paper][Note]( Ian Goodfellow Paper)

heavy_check_mark [Improved Techniques for Training GANs] [Paper][Code](Goodfellow's paper)

heavy_check_mark [Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks] [Paper](ICLR)

heavy_check_mark [Semi-Supervised QA with Generative Domain-Adaptive Nets] [Paper](ACL 2017)

heavy_check_mark [Good Semi-supervised Learning that Requires a Bad GAN] [Paper][Code](NIPS 2017)


heavy_check_mark [AdaGAN: Boosting Generative Models] [Paper][[Code]](Google Brain)

Image blending

heavy_check_mark [GP-GAN: Towards Realistic High-Resolution Image Blending] [Paper][Code]

Image Inpainting

heavy_check_mark [Semantic Image Inpainting with Perceptual and Contextual Losses] [Paper][Code](CVPR 2017)

heavy_check_mark [Context Encoders: Feature Learning by Inpainting] [Paper][Code]

heavy_check_mark [Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks] [Paper]

heavy_check_mark [Generative face completion] [Paper][code](CVPR2017)

heavy_check_mark [Globally and Locally Consistent Image Completion] [MainPAGE][code](SIGGRAPH 2017)

heavy_check_mark [High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis] [Paper][code](CVPR 2017)

heavy_check_mark [Eye In-Painting with Exemplar Generative Adversarial Networks] [Paper][Introduction][Tensorflow code](CVPR2018)

heavy_check_mark [Generative Image Inpainting with Contextual Attention] [Paper][Project][Demo][YouTube][Code](CVPR2018)

heavy_check_mark [Free-Form Image Inpainting with Gated Convolution] [Paper][Project][YouTube]


heavy_check_mark [Pose-Normalized Image Generation for Person Re-identification] [Paper][Code](ECCV 2018)


heavy_check_mark [Image super-resolution through deep learning ][Code](Just for face dataset)

heavy_check_mark [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network] [Paper][Code](Using Deep residual network)

heavy_check_mark [EnhanceGAN] [Docs][[Code]]

heavy_check_mark [ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks] [Paper][Code](ECCV 2018 workshop)


heavy_check_mark [Robust LSTM-Autoencoders for Face De-Occlusion in the Wild] [Paper]

Semantic Segmentation

heavy_check_mark [Adversarial Deep Structural Networks for Mammographic Mass Segmentation] [Paper][Code]

heavy_check_mark [Semantic Segmentation using Adversarial Networks] [Paper](soumith's paper)

Object Detection

heavy_check_mark [Perceptual generative adversarial networks for small object detection] [Paper](CVPR 2017)

heavy_check_mark [A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection] [Paper][code](CVPR2017)

Conditional adversarial

heavy_check_mark [Conditional Generative Adversarial Nets] [Paper][Code]

heavy_check_mark [InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets] [Paper][Code][Code]

heavy_check_mark [Conditional Image Synthesis With Auxiliary Classifier GANs] [Paper][Code](GoogleBrain ICLR 2017)

heavy_check_mark [Pixel-Level Domain Transfer] [Paper][Code]

heavy_check_mark [Invertible Conditional GANs for image editing] [Paper][Code]

heavy_check_mark [Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space] [Paper][Code]

heavy_check_mark [StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks] [Paper][Code]

Video Prediction and Generation

heavy_check_mark [Deep multi-scale video prediction beyond mean square error] [Paper][Code](Yann LeCun's paper)

heavy_check_mark [Generating Videos with Scene Dynamics] [Paper][Web][Code]

heavy_check_mark [MoCoGAN: Decomposing Motion and Content for Video Generation] [Paper]

Texture Synthesis & style transfer

heavy_check_mark [Precomputed real-time texture synthesis with markovian generative adversarial networks] [Paper][Code](ECCV 2016)

Image translation


heavy_check_mark [Image-to-image translation using conditional adversarial nets] [Paper][Code][Code]

heavy_check_mark [Learning to Discover Cross-Domain Relations with Generative Adversarial Networks] [Paper][Code]

heavy_check_mark [Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks] [Paper][Code]

heavy_check_mark [CoGAN: Coupled Generative Adversarial Networks] [Paper][Code](NIPS 2016)

heavy_check_mark [Unsupervised Image-to-Image Translation with Generative Adversarial Networks] [Paper](NIPS 2017)

heavy_check_mark [Unsupervised Image-to-Image Translation Networks] [Paper]

heavy_check_mark [Triangle Generative Adversarial Networks] [Paper]

heavy_check_mark [High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs] [Paper][code]

heavy_check_mark [XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings] [Paper](Reviewed)

heavy_check_mark [UNIT: UNsupervised Image-to-image Translation Networks] [Paper][Code](NIPS 2017)

heavy_check_mark [Toward Multimodal Image-to-Image Translation] [Paper][Code](NIPS 2017)

heavy_check_mark [Multimodal Unsupervised Image-to-Image Translation] [Paper][Code]

heavy_check_mark [Video-to-Video Synthesis] [Paper][Code]

Facial Attribute Manipulation

heavy_check_mark [Autoencoding beyond pixels using a learned similarity metric] [Paper][code][Tensorflow code]

heavy_check_mark [Coupled Generative Adversarial Networks] [Paper][Caffe Code][Tensorflow Code](NIPS)

heavy_check_mark [Invertible Conditional GANs for image editing] [Paper][Code]

heavy_check_mark [Learning Residual Images for Face Attribute Manipulation] [Paper][code](CVPR 2017)

heavy_check_mark [Neural Photo Editing with Introspective Adversarial Networks] [Paper][Code](ICLR 2017)

heavy_check_mark [Neural Face Editing with Intrinsic Image Disentangling] [Paper](CVPR 2017)

heavy_check_mark [GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data ] [Paper][code](BMVC 2017)

heavy_check_mark [ST-GAN: Unsupervised Facial Image Semantic Transformation Using Generative Adversarial Networks] [Paper]

heavy_check_mark [Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis] [Paper](ICCV 2017)

heavy_check_mark [StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation] [Paper][code](CVPR 2018)

heavy_check_mark [Arbitrary Facial Attribute Editing: Only Change What You Want] [Paper][code]

heavy_check_mark [ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes] [Paper][code](ECCV 2018)

heavy_check_mark [Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation] [Paper][code](ACM MM2018 oral)

heavy_check_mark [GANimation: Anatomically-aware Facial Animation from a Single Image] [Paper][code](ECCV 2018 oral)

Reinforcement learning

heavy_check_mark [Connecting Generative Adversarial Networks and Actor-Critic Methods] [Paper](NIPS 2016 workshop)


heavy_check_mark [C-RNN-GAN: Continuous recurrent neural networks with adversarial training] [Paper][Code] heavy_check_mark [SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient] [Paper][Code](AAAI 2017)


heavy_check_mark [Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery] [Paper]


heavy_check_mark [Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling] [Paper][Web][code](2016 NIPS)

heavy_check_mark [Transformation-Grounded Image Generation Network for Novel 3D View Synthesis] [Web](CVPR 2017)


heavy_check_mark [MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation using 1D and 2D Conditions] [Paper][HOMEPAGE]

For discrete distributions

heavy_check_mark [Maximum-Likelihood Augmented Discrete Generative Adversarial Networks] [Paper]

heavy_check_mark [Boundary-Seeking Generative Adversarial Networks] [Paper]

heavy_check_mark [GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution] [Paper]

Improving Classification And Recong

heavy_check_mark [Generative OpenMax for Multi-Class Open Set Classification] [Paper](BMVC 2017)

heavy_check_mark [Controllable Invariance through Adversarial Feature Learning] [Paper][code](NIPS 2017)

heavy_check_mark [Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro] [Paper][Code] (ICCV2017)

heavy_check_mark [Learning from Simulated and Unsupervised Images through Adversarial Training] [Paper][code](Apple paper, CVPR 2017 Best Paper)


heavy_check_mark [cleverhans] [Code](A library for benchmarking vulnerability to adversarial examples)

heavy_check_mark [reset-cppn-gan-tensorflow] [Code](Using Residual Generative Adversarial Networks and Variational Auto-encoder techniques to produce high resolution images)

heavy_check_mark [HyperGAN] [Code](Open source GAN focused on scale and usability)


inFERENCeAdversarial network
distillDeconvolution and Image Generation
yingzhenliGan theory
OpenAIGenerative model


heavy_check_mark [1] (NIPS Goodfellow Slides)[Chinese Trans][details]

heavy_check_mark [2] [PDF](NIPS Lecun Slides)

heavy_check_mark [3] [ICCV 2017 Tutorial About GANS]