AdversarialNetsPapers

The classic about Generative Adversarial Networks

First paper

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

Image Translation

[UNSUPERVISED CROSS-DOMAIN IMAGE GENERATION] [Paper][Code]

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

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

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

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

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

[DualGAN: Unsupervised Dual Learning for Image-to-Image Translation] [Paper](NIPS 2017)[Code]

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

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

[XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings] [Paper]

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

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

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

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

[Everybody Dance Now] [Paper][Code]

[GestureGAN for Hand Gesture-to-Gesture Translation in the Wild] [Paper][Code](ACMMM 2018)

[Art2Real: Unfolding the Reality of Artworks via Semantically-Aware Image-to-Image Translation] [Paper](CVPR 2019)

[Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation] [Paper][Code](CVPR 2019 oral)

[Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation] [Paper][Code](CVPR 2020)

[StarGAN v2: Diverse Image Synthesis for Multiple Domains] [Paper][Code](CVPR 2020)

[Structural-analogy from a Single Image Pair] [Paper][Code]

[High-Resolution Daytime Translation Without Domain Labels] [Paper][Code]

AutoML

[AutoGAN: Neural Architecture Search for Generative Adversarial Networks] [Paper][Code](ICCV 2019)

Gaze Correction and Redirection

[DeepWarp: Photorealistic Image Resynthesis for Gaze Manipulation] [Paper][code](ECCV 2016)

[Photo-Realistic Monocular Gaze Redirection Using Generative Adversarial Networks] [Paper][Code](ICCV 2019)

[GazeCorrection:Self-Guided Eye Manipulation in the wild using Self-Supervised Generative Adversarial Networks] [Paper][code]

[MGGR: MultiModal-Guided Gaze Redirection with Coarse-to-Fine Learning] [Paper]

Image Animation

[Animating arbitrary objects via deep motion transfer] [Paper][code](CVPR 2019)

[First Order Motion Model for Image Animation] [Paper][code](NIPS 2019)

Facial Attribute Manipulation

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[Geometry Guided Adversarial Facial Expression Synthesis] [Paper](ACMMM 2018)

[STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing] [Paper][code](CVPR 2019)

[3d guided fine-grained face manipulation] [Paper](CVPR 2019)

[SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color] [Paper][code](ICCV 2019)

Generation High-Quality Images

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

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

[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]

Unclassified

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

[Adversarial Autoencoders] [Paper][Code]

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

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

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

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

[Adversarial Training for Sketch Retrieval] [Paper]

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

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

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

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

[Adversarial Feature Learning] [Paper]

[Adversarially Learned Inference][Paper][Code]

GAN Theory

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

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

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

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

[Sampling Generative Networks] [Paper][Code]

[How to train Gans] [Docu]

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

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

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

[Wasserstein GAN] [Paper][Code]

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

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

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

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

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

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

[Self-Supervised Generative Adversarial Networks][Paper][code]（CVPR 2019）

Scene Generation

[a layer-based sequential framework for scene generation with gans] [Paper][Code](AAAI 2019)

Semi-Supervised Learning

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

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

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

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

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

Ensemble

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

Image blending

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

Image Inpainting

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

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

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

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

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

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

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

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

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

[EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning] [Paper][Code]

Re-identification

[Joint Discriminative and Generative Learning for Person Re-identification] [Paper][Code][YouTube] [Bilibili] (CVPR2019 Oral)

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

Super-Resolution

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

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

[EnhanceGAN] [Docs][[Code]]

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

De-Occlusion

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

Semantic Segmentation

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

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

Object Detection

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

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

Landmark Detection

[Style aggregated network for facial landmark detection] [Paper](CVPR 2018)

Conditional Adversarial

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

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

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

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

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

[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]

Video Prediction and Generation

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

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

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

Texture Synthesis & style transfer

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

[Controllable Artistic Text Style Transfer via Shape-Matching GAN] [Paper][Code](ICCV 2019)

Shadow Detection and Removal

[ARGAN: Attentive Recurrent Generative Adversarial Network for Shadow Detection and Removal] [Paper][Code](ICCV 2019)

Makeup

[BeautyGAN: Instance-level Facial Makeup Transfer with Deep Generative Adversarial Network] [Paper](ACMMM 2018)

Reinforcement learning

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

RNN

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

Medicine

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

3D

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

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

MUSIC

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

For discrete distributions

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

[Boundary-Seeking Generative Adversarial Networks] [Paper]

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

Improving Classification And Recong

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

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

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

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

[GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification] [Paper] (Neurocomputing Journal (2018), Elsevier）

Project

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

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

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

Blogs

Tutorial

[1] http://www.iangoodfellow.com/slides/2016-12-04-NIPS.pdf (NIPS Goodfellow Slides)[Chinese Trans][details]

[2] [PDF](NIPS Lecun Slides)

[3] [ICCV 2017 Tutorial About GANS]