BaiFree/AdversarialNetsPapers

Awesome paper list with code about generative adversarial nets

AdversarialNetsPapers

Awesome papers about Generative Adversarial Networks. Majority of papers are related to Image Translation.

Contributing

Please help contribute this list by contacting [Me][zhang163220@gmail.com] or add pull request

Table of Contents

• First Paper
• [Application]
  • Image Translation
  • Facial Attribute Manipulation
  • Face Swap and Reenactment
  • Gaze Correction and Redirection
  • Person Image Synthesis
  • Image Inpainting
  • Scene Generation
  • Image blending
  • Re-identification
  • Super-Resolution
  • De-Occlusion
  • Semantic-Segmentation
  • Object-Detection
  • Landmark-Detection
  • Video-Prediction-and-Generation
  • Shadow Detection and Removal
  • Makeup
  • 3D
  • Improving Classification And Recong
• [Theory]
  • Generative Models
  • GAN Theory
• [Machine Learning]
  • Conditional-Adversarial
  • Semi-Supervised Learning
  • Ensemble
• [Others]
  • AutoML
  • Reinforcement learning
  • Discrete Distributions
  • RNN
• [Interdisciplinary]
  • Medicine
  • MUSIC
• [Tutorial]
  • Project
  • Blogs
  • Tutorial

First paper

✔️ [Generative Adversarial Nets]

• [Paper][Code](NIPS 2014)

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]

✔️ [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]

✔️ [Rethinking the Truly Unsupervised Image-to-Image Translation]

• [Paper][Code]

✔️ [Diverse Image Generation via Self-Conditioned GANs]

• [Paper][Code](CVPR2020)

✔️ [Contrastive Learning for Unpaired Image-to-Image Translation]

• [Paper][Code](ECCV2020)

Facial Attribute Manipulation

✔️ [Autoencoding beyond pixels using a learned similarity metric]

• [Paper][code][Tensorflow code](ICML 2016）

✔️ [Coupled Generative Adversarial Networks]

• [Paper][Caffe Code][Tensorflow Code](NIPS 2016）

✔️ [Invertible Conditional GANs for image editing]

• [Paper][Code](Arxiv 2016)

✔️ [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)

✔️ [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](TIP 2019)

✔️ [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](ACM MM2018)

✔️ [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)

✔️ [A Survey of Deep Facial Attribute Analysis]

• [Paper](IJCV 2019)

✔️ [PA-GAN: Progressive Attention Generative Adversarial Network for Facial Attribute Editing]

• [Paper][code]（Arxiv 2020）

✔️ [SSCGAN: Facial Attribute Editing via StyleSkip Connections]

• [Paper](ECCV 2020)

✔️ [CAFE-GAN: Arbitrary Face Attribute Editingwith Complementary Attention Feature]

• [Paper](ECCV 2020)

Generative Models

✔️ [Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks]

• [Paper][Code](Gan with convolutional networks)(ICLR 2015)

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

• [Paper][Code](NIPS 2015)

✔️ [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]

• [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]

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]

✔️ [Dual In-painting Model for Unsupervised Gaze Correction and Animation in the Wild]

• [Paper][Code](ACM MM2020)

AutoML

✔️ [AutoGAN: Neural Architecture Search for Generative Adversarial Networks]

• [Paper][Code](ICCV 2019)

Image Animation

✔️ [Animating arbitrary objects via deep motion transfer]

• [Paper][code](CVPR 2019)

✔️ [First Order Motion Model for Image Animation]

• [Paper][code](NIPS 2019)

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）

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]

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]

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]

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]

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

Author	Address
inFERENCe	Adversarial network
inFERENCe	InfoGan
distill	Deconvolution and Image Generation
yingzhenli	Gan theory
OpenAI	Generative model

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]