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https://github.com/eric-erki/really-awesome-gan

A list of papers on Generative Adversarial (Neural) Networks
https://github.com/eric-erki/really-awesome-gan
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A list of papers on Generative Adversarial (Neural) Networks
Host: GitHub
URL: https://github.com/eric-erki/really-awesome-gan
Owner: eric-erki
Created: 2020-02-02T10:00:21.000Z (almost 5 years ago)
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README

        # really-awesome-gan

A list of papers and other resources on Generative Adversarial (Neural) Networks.

This site is maintained by Holger Caesar.

To complement or correct it, please contact me at holger-at-it-caesar.com or visit [it-caesar.com](http://www.it-caesar.com). Also checkout [really-awesome-semantic-segmentation](https://github.com/nightrome/really-awesome-semantic-segmentation) and our [COCO-Stuff dataset](https://github.com/nightrome/cocostuff).

**NOTE:** Despite the enormous interest in this cite (~3000 visitors per month), I will no longer add new papers starting from November 2017. I feel that GANs have come from an exotic topic to the mainstream and an exhaustive list of all GAN papers is no more feasible or useful. However, I invite other people to continue this effort and reuse my list.

## Contents

- [Recommendations](#recommendations)

- [Workshops](#workshops)

- [Tutorials & Workshops & Blogs](#tutorials--workshops--blogs)

- [Videos](#videos)

- [Code](#code)

- [Papers](#papers)

  - [Overview](#overview)

  - [Theory & Machine Learning](#theory--machine-learning)

  - [Applied Vision](#applied-vision)

  - [Applied Other](#applied-other)

  - [Humor](#humor)

  

## Recommendations



Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis [arXiv] 





Pose Guided Person Image Generation [arXiv] 





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







# Tutorials & Workshops & Blogs

- Columbia Advanced Machine Learning Seminar

  - New Progress on GAN Theory and Practice [[Blog]](https://casmls.github.io/general/2017/04/13/gan.html)

  - Implicit Generative Models — What are you GAN-na do? [[Blog]](https://casmls.github.io/general/2017/05/24/ligm.html)

- How to Train a GAN? Tips and tricks to make GANs work [[Blog]](https://github.com/soumith/ganhacks)

- NIPS 2016 Tutorial: Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1701.00160)

- NIPS 2016 Workshop on Adversarial Training [[Web]](https://sites.google.com/site/nips2016adversarial/) [[Blog]](http://www.inference.vc/my-summary-of-adversarial-training-nips-workshop/)

- On the intuition behind deep learning & GANs — towards a fundamental understanding [[Blog]](https://blog.waya.ai/introduction-to-gans-a-boxing-match-b-w-neural-nets-b4e5319cc935)

- OpenAI - Generative Models [[Blog]](https://openai.com/blog/generative-models/)

- SimGANs - a game changer in unsupervised learning, self driving cars, and more [[Blog]](https://blog.waya.ai/simgans-applied-to-autonomous-driving-5a8c6676e36b)

- Deep Diving into GANs: from theory to production (EuroScipy 2018) [[GitHub]](https://github.com/zurutech/gans-from-theory-to-production) 

# Books

- GANs in Action: Deep learning with Generative Adversarial Networks [[Book]](https://www.manning.com/books/gans-in-action)

# Videos

- Generative Adversarial Networks by Ian Goodfellow [[Video]](https://channel9.msdn.com/Events/Neural-Information-Processing-Systems-Conference/Neural-Information-Processing-Systems-Conference-NIPS-2016/Generative-Adversarial-Networks)

- Tutorial on Generative Adversarial Networks by Mark Chang [[Video]](https://www.youtube.com/playlist?list=PLeeHDpwX2Kj5Ugx6c9EfDLDojuQxnmxmU)

- Deep Diving into GANs: From Theory to Production (EuroSciPy 2018) by Michele De Simoni, Paolo Galeone [[Video]](https://www.youtube.com/watch?v=CePrdabdtxw) 

# Code

- Cleverhans: A library for benchmarking vulnerability to adversarial examples [[Code]](https://github.com/openai/cleverhans) [[Blog]](http://cleverhans.io/)

- Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch) [[Blog]](https://medium.com/@devnag/generative-adversarial-networks-gans-in-50-lines-of-code-pytorch-e81b79659e3f) [[Code]](https://github.com/devnag/pytorch-generative-adversarial-networks)

- Generative Models: Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow [[Code]](https://github.com/wiseodd/generative-models)

# Papers

## Overview

- Generative Adversarial Networks: An Overview [[arXiv]](https://arxiv.org/abs/1710.07035)

## Theory & Machine Learning

- A Classification-Based Perspective on GAN Distributions [[arXiv]](https://arxiv.org/abs/1711.00970)

- A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models [[arXiv]](https://arxiv.org/abs/1611.03852)

- A General Retraining Framework for Scalable Adversarial Classification [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_2.pdf)

- Activation Maximization Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1703.02000)

- AdaGAN: Boosting Generative Models [[arXiv]](https://arxiv.org/abs/1701.02386)

- Adversarial Autoencoders [[arXiv]](https://arxiv.org/abs/1511.05644)

- Adversarial Discriminative Domain Adaptation [[arXiv]](https://arxiv.org/abs/1702.05464)

- Adversarial Generator-Encoder Networks [[arXiv]](https://arxiv.org/pdf/1704.02304.pdf)

- Adversarial Feature Learning [[arXiv]](https://arxiv.org/abs/1605.09782) [[Code]](https://github.com/wiseodd/generative-models)

- Adversarially Learned Inference [[arXiv]](https://arxiv.org/abs/1606.00704) [[Code]](https://github.com/wiseodd/generative-models)

- AE-GAN: adversarial eliminating with GAN [[arXiv]](https://arxiv.org/abs/1707.05474)

- An Adversarial Regularisation for Semi-Supervised Training of Structured Output Neural Networks [[arXiv]](https://arxiv.org/abs/1702.02382)

- APE-GAN: Adversarial Perturbation Elimination with GAN [[arXiv]](https://arxiv.org/abs/1707.05474)

- Associative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.06953)

- Autoencoding beyond pixels using a learned similarity metric [[arXiv]](https://arxiv.org/abs/1512.09300)

- Bayesian Conditional Generative Adverserial Networks [[arXiv]](https://arxiv.org/abs/1706.05477)

- Bayesian GAN [[arXiv]](https://arxiv.org/abs/1705.09558)

- BEGAN: Boundary Equilibrium Generative Adversarial Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_4.pdf) [[arXiv]](https://arxiv.org/abs/1703.10717) [[Code]](https://github.com/wiseodd/generative-models)

- Binary Generative Adversarial Networks for Image Retrieval [[arXiv]](https://arxiv.org/abs/1708.04150)

- Boundary-Seeking Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1702.08431) [[Code]](https://github.com/wiseodd/generative-models)

- CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training [[arXiv]](https://arxiv.org/abs/1709.02023)

- Class-Splitting Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.07359)

- Comparison of Maximum Likelihood and GAN-based training of Real NVPs [[arXiv]](https://arxiv.org/abs/1705.05263)

- Conditional CycleGAN for Attribute Guided Face Image Generation [[arXiv]](https://arxiv.org/abs/1705.09966)

- Conditional Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1411.1784) [[Code]](https://github.com/wiseodd/generative-models)

- Connecting Generative Adversarial Networks and Actor-Critic Methods [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_1.pdf)

- Continual Learning in Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1705.08395)

- C-RNN-GAN: Continuous recurrent neural networks with adversarial training [[arXiv]](https://arxiv.org/abs/1611.09904)

- CM-GANs: Cross-modal Generative Adversarial Networks for Common Representation Learning [[arXiv]](https://arxiv.org/abs/1710.05106)

- Cooperative Training of Descriptor and Generator Networks [[arXiv]](https://arxiv.org/abs/1609.09408)

- Coupled Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1606.07536) [[Code]](https://github.com/wiseodd/generative-models)

- Dualing GANs [[arXiv]](https://arxiv.org/abs/1706.06216)

- Deep and Hierarchical Implicit Models [[arXiv]](https://arxiv.org/abs/1702.08896)

- Energy-based Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1609.03126) [[Code]](https://github.com/wiseodd/generative-models)

- Explaining and Harnessing Adversarial Examples [[arXiv]](https://arxiv.org/abs/1412.6572)

- Flow-GAN: Bridging implicit and prescribed learning in generative models [[arXiv]](https://arxiv.org/abs/1705.08868)

- f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization [[arXiv]](https://arxiv.org/abs/1606.00709) [[Code]](https://github.com/wiseodd/generative-models)

- Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking [[arXiv]](https://arxiv.org/abs/1704.04865)

- Generalization and Equilibrium in Generative Adversarial Nets (GANs) [[arXiv]](https://arxiv.org/abs/1703.00573)

- Generating images with recurrent adversarial networks [[arXiv]](https://arxiv.org/abs/1602.05110)

- Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1406.2661) [[Code]](https://github.com/goodfeli/adversarial) [[Code]](https://github.com/wiseodd/generative-models)

- Generative Adversarial Networks as Variational Training of Energy Based Models [[arXiv]](https://arxiv.org/abs/1611.01799)

- Generative Adversarial Networks with Inverse Transformation Unit [[arXiv]](https://arxiv.org/abs/1709.09354)

- Generative Adversarial Parallelization [[arXiv]](https://arxiv.org/abs/1612.04021) [[Code]](https://github.com/wiseodd/generative-models)

- Generative Adversarial Residual Pairwise Networks for One Shot Learning [[arXiv]](https://arxiv.org/abs/1703.08033)

- Generative Adversarial Structured Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_14.pdf)

- Generative Cooperative Net for Image Generation and Data Augmentation [[arXiv]](https://arxiv.org/abs/1705.02887)

- Generative Moment Matching Networks [[arXiv]](https://arxiv.org/abs/1502.02761) [[Code]](https://github.com/yujiali/gmmn)

- Generative Semantic Manipulation with Contrasting GAN [[arXiv]](https://arxiv.org/abs/1708.00315)

- Geometric GAN [[arXiv]](https://arxiv.org/abs/1705.02894)

- Good Semi-supervised Learning that Requires a Bad GAN [[arXiv]](https://arxiv.org/abs/1705.09783)

- Gradient descent GAN optimization is locally stable [[arXiv]](https://arxiv.org/abs/1706.04156)

- How to Train Your DRAGAN [[arXiv]](https://arxiv.org/abs/1705.07215)

- Image Quality Assessment Techniques Show Improved Training and Evaluation of Autoencoder Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1708.02237)

- Improved Semi-supervised Learning with GANs using Manifold Invariances [[arXiv]](https://arxiv.org/abs/1705.08850)

- Improved Techniques for Training GANs [[arXiv]](https://arxiv.org/abs/1606.03498) [[Code]](https://github.com/openai/improved-gan)

- Improved Training of Wasserstein GANs [[arXiv]](https://arxiv.org/abs/1704.00028) [[Code]](https://github.com/wiseodd/generative-models)

- InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1606.03657) [[Code]](https://github.com/wiseodd/generative-models)

- Inverting The Generator Of A Generative Adversarial Network [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_9.pdf)

- It Takes (Only) Two: Adversarial Generator-Encoder Networks [[arXiv]](https://arxiv.org/abs/1704.02304)

- KGAN: How to Break The Minimax Game in GAN [[arXiv]](https://arxiv.org/abs/1711.01744)

- Learning in Implicit Generative Models [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_10.pdf)

- Learning Loss for Knowledge Distillation with Conditional Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.00513)

- Learning to Discover Cross-Domain Relations with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.05192) [[Code]](https://github.com/wiseodd/generative-models)

- Learning Texture Manifolds with the Periodic Spatial GAN [[arXiv]](https://arxiv.org/abs/1705.06566)

- Least Squares Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.04076) [[Code]](https://github.com/wiseodd/generative-models)

- Linking Generative Adversarial Learning and Binary Classification [[arXiv]](https://arxiv.org/abs/1709.01509)

- Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities [[arXiv]](https://arxiv.org/abs/1701.06264)

- LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation [[arXiv]](https://arxiv.org/abs/1703.01560)

- MAGAN: Margin Adaptation for Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.03817) [[Code]](https://github.com/wiseodd/generative-models)

- Maximum-Likelihood Augmented Discrete Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1702.07983)

- McGan: Mean and Covariance Feature Matching GAN [[arXiv]](https://arxiv.org/abs/1702.08398)

- Message Passing Multi-Agent GANs [[arXiv]](https://arxiv.org/abs/1612.01294)

- MMD GAN: Towards Deeper Understanding of Moment Matching Network [[arXiv]](https://arxiv.org/abs/1705.08584)

- Mode Regularized Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1612.02136) [[Code]](https://github.com/wiseodd/generative-models)

- Multi-Agent Diverse Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.02906)

- Multi-Generator Gernerative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1708.02556)

- Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models [[arXiv]](https://arxiv.org/abs/1705.10843)

- On Convergence and Stability of GANs [[arXiv]](https://arxiv.org/abs/1705.07215)

- On the effect of Batch Normalization and Weight Normalization in Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.03971)

- On the Quantitative Analysis of Decoder-Based Generative Models [[arXiv]](https://arxiv.org/abs/1611.04273)

- Optimizing the Latent Space of Generative Networks [[arXiv]](https://arxiv.org/abs/1707.05776)

- Parametrizing filters of a CNN with a GAN [[arXiv]](https://arxiv.org/abs/1710.11386)

- PixelGAN Autoencoders [[arXiv]](https://arxiv.org/abs/1706.00531)

- Progressive Growing of GANs for Improved Quality, Stability, and Variation [[arXiv]](https://arxiv.org/abs/1710.10196) [[Code]](https://github.com/tkarras/progressive_growing_of_gans)

- SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation [[arXiv]](https://arxiv.org/abs/1706.01805)

- SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient [[arXiv]](https://arxiv.org/abs/1609.05473)

- Simple Black-Box Adversarial Perturbations for Deep Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_11.pdf)

- Softmax GAN [[arXiv]](https://arxiv.org/abs/1704.06191)

- Stabilizing Training of Generative Adversarial Networks through Regularization [[arXiv]](https://arxiv.org/abs/1705.09367)

- Stacked Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1612.04357)

- Statistics of Deep Generated Images [[arXiv]](https://arxiv.org/abs/1708.02688)

- Structured Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1711.00889)

- Tensorizing Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1710.10772)

- The Cramer Distance as a Solution to Biased Wasserstein Gradients [[arXiv]](https://arxiv.org/abs/1705.10743)

- Towards Understanding Adversarial Learning for Joint Distribution Matching [[arXiv]](https://arxiv.org/abs/1709.01215)

- Training generative neural networks via Maximum Mean Discrepancy optimization [[arXiv]](https://arxiv.org/abs/1505.03906)

- Triple Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1703.02291)

- Unrolled Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.02163)

- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1511.06434) [[Code]](https://github.com/Newmu/dcgan_code) [[Code]](https://github.com/pytorch/examples/tree/master/dcgan) [[Code]](https://github.com/carpedm20/DCGAN-tensorflow) [[Code]](https://github.com/soumith/dcgan.torch) [[Code]](https://github.com/jacobgil/keras-dcgan)

- Wasserstein GAN [[arXiv]](https://arxiv.org/abs/1701.07875) [[Code]](https://github.com/martinarjovsky/WassersteinGAN) [[Code]](https://github.com/wiseodd/generative-models)

## Applied Vision

- 3D Object Reconstruction from a Single Depth View with Adversarial Learning [[arXiv]](https://arxiv.org/abs/1708.07969)

- 3D Shape Induction from 2D Views of Multiple Objects [[arXiv]](https://arxiv.org/abs/1612.05872)

- A step towards procedural terrain generation with GANs [[arXiv]](https://arxiv.org/abs/1707.03383) [[Code]](https://github.com/christopher-beckham/gan-heightmaps)

- Abnormal Event Detection in Videos using Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1708.09644)

- Adversarial Generation of Training Examples for Vehicle License Plate Recognition [[arXiv]](https://arxiv.org/abs/1707.03124)

- Adversarial nets with perceptual losses for text-to-image synthesis [[arXiv]](https://arxiv.org/abs/1708.09321)

- Adversarial Networks for Spatial Context-Aware Spectral Image Reconstruction from RGB [[arXiv]](https://arxiv.org/abs/1709.00265)

- Adversarial Networks for the Detection of Aggressive Prostate Cancer [[arXiv]](https://arxiv.org/abs/1702.08014)

- Adversarial PoseNet: A Structure-aware Convolutional Network for Human Pose Estimation [[arXiv]](https://arxiv.org/pdf/1705.00389.pdf)

- Adversarial Training For Sketch Retrieval [[arXiv]](https://arxiv.org/abs/1607.02748)

- Aesthetic-Driven Image Enhancement by Adversarial Learning [[arXiv]](https://arxiv.org/abs/1707.05251)

- Age Progression / Regression by Conditional Adversarial Autoencoder [[arXiv]](https://arxiv.org/abs/1702.08423)

- AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.01400)

- Amortised MAP Inference for Image Super-resolution [[arXiv]](https://arxiv.org/abs/1610.04490)

- Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network [[arXiv]](https://arxiv.org/abs/1811.00344) [[Code]](https://github.com/subeeshvasu/2018_subeesh_epsr_eccvw)

- A Novel Approach to Artistic Textual Visualization via GAN [[arXiv]](https://arxiv.org/abs/1710.10553)

- Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification [[arXiv]](https://arxiv.org/abs/1709.03654)

- Arbitrary Facial Attribute Editing: Only Change What You Want [[arXiv]](https://arxiv.org/abs/1711.10678) [[Code]](https://github.com/LynnHo/AttGAN-Tensorflow)

- ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1709.00938)

- ArtGAN: Artwork Synthesis with Conditional Categorial GANs [[arXiv]](https://arxiv.org/abs/1702.03410)

- Artificial Generation of Big Data for Improving Image Classification: A Generative Adversarial Network Approach on SAR Data [[arXiv]](https://arxiv.org/abs/1711.02010)

- Auto-Encoder Guided GAN for Chinese Calligraphy Synthesis [[arXiv]](https://arxiv.org/abs/1706.08789)

- Auto-painter: Cartoon Image Generation from Sketch by Using Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1705.01908)

- Automatic Liver Segmentation Using an Adversarial Image-to-Image Network [[arXiv]](https://arxiv.org/abs/1707.08037)

- Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis [[arXiv]](https://arxiv.org/abs/1704.04086)

- CAN: Creative Adversarial Networks Generating “Art” by Learning About Styles and Deviating from Style Norms [[arXiv]](https://arxiv.org/abs/1706.07068)

- CompoNet: Learning to Generate the Unseen by Part Synthesis and Composition [[arXiv]](https://arxiv.org/abs/1811.07441) [[Code]](https://github.com/nschor/CompoNet)

- Compressed Sensing MRI Reconstruction with Cyclic Loss in Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.00753)

- Conditional Adversarial Network for Semantic Segmentation of Brain Tumor [[arXiv]](https://arxiv.org/abs/1708.05227)

- Conditional generative adversarial nets for convolutional face generation [[Paper]](http://www.foldl.me/uploads/2015/conditional-gans-face-generation/paper.pdf)

- Conditional Image Synthesis with Auxiliary Classifier GANs [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_7.pdf) [[arXiv]](https://arxiv.org/abs/1610.09585) [[Code]](https://github.com/wiseodd/generative-models)

- Contextual RNN-GANs for Abstract Reasoning Diagram Generation [[arXiv]](https://arxiv.org/abs/1609.09444)

- Controllable Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1708.00598)

- Creatism: A deep-learning photographer capable of creating professional work [[arXiv]](https://arxiv.org/abs/1707.03491)

- Crossing Nets: Combining GANs and VAEs with a Shared Latent Space for Hand Pose Estimation [[arXiv]](https://arxiv.org/abs/1702.03431)

- CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training [[arXiv]](https://arxiv.org/abs/1703.10155)

- Data Augmentation in Classification using GAN [[arXiv]](https://arxiv.org/abs/1711.00648)

- Deep Generative Adversarial Compression Artifact Removal [[arXiv]](https://arxiv.org/abs/1704.02518)

- Deep Generative Adversarial Networks for Compressed Sensing (GANCS) Automates MRI [[arXiv]](https://arxiv.org/abs/1706.00051)

- Deep Generative Adversarial Neural Networks for Realistic Prostate Lesion MRI Synthesis [[arXiv]](https://arxiv.org/abs/1708.00129)

- Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks [[arXiv]](https://arxiv.org/abs/1506.05751) [[Code]](https://github.com/facebook/eyescream) [[Blog]](http://soumith.ch/eyescream/)

- Deep multi-scale video prediction beyond mean square error [[arXiv]](https://arxiv.org/abs/1511.05440) [[Code]](https://github.com/dyelax/Adversarial_Video_Generation)

- Deep Unsupervised Representation Learning for Remote Sensing Images [[arXiv]](https://arxiv.org/abs/1612.08879)

- DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data [[arXiv]](https://arxiv.org/abs/1706.02071)

- Depth Structure Preserving Scene Image Generation [[arXiv]](https://arxiv.org/abs/1706.00212)

- DualGAN: Unsupervised Dual Learning for Image-to-Image Translation [[arXiv]](https://arxiv.org/abs/1704.02510) [[Code]](https://github.com/wiseodd/generative-models)

- Dual Motion GAN for Future-Flow Embedded Video Prediction [[arXiv]](https://arxiv.org/abs/1708.00284)

- Efficient Super Resolution For Large-Scale Images Using Attentional GAN [[arXiv]](https://arxiv.org/abs/1812.04821) [[Thesis]](https://digitalcommons.wpi.edu/etd-theses/1256/) [[Thesis]](https://www.wpi.edu/news/announcements/data-science-ms-thesis-presentation-xiaozhou-zou)

- ExprGAN: Facial Expression Editing with Controllable Expression Intensity [[arXiv]](https://arxiv.org/abs/1709.03842)

- Face Aging With Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1702.01983)

- Face Transfer with Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1710.06090)

- Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1710.04835)

- Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.05392)

- From source to target and back: symmetric bi-directional adaptive GAN [[arXiv]](https://arxiv.org/abs/1705.08824)

- Full Resolution Image Compression with Recurrent Neural Networks [[arXiv]](https://arxiv.org/abs/1608.05148)

- GANs for Biological Image Synthesis [[arXiv]](https://arxiv.org/abs/1708.04692)

- GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data [[arXiv]](https://arxiv.org/abs/1705.04932) [[Code]](https://github.com/Prinsphield/GeneGAN)

- Generate Identity-Preserving Faces by Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1706.03227)

- Generate To Adapt: Aligning Domains using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.01705)

- Generative Adversarial Models for People Attribute Recognition in Surveillance [[arXiv]](https://arxiv.org/abs/1707.02240)

- Generative Adversarial Network based on Resnet for Conditional Image Restoration [[arxiv]](https://arxiv.org/abs/1707.04881)

- Generative Adversarial Network-based Synthesis of Visible Faces from Polarimetric Thermal Faces [[arXiv]](https://arxiv.org/abs/1708.02681)

- Generative Adversarial Networks for Multimodal Representation Learning in Video Hyperlinking [[arXiv]](https://arxiv.org/abs/1705.05103)

- Generative Adversarial Text to Image Synthesis [[arXiv]](https://arxiv.org/abs/1605.05396) [[Code]](https://github.com/paarthneekhara/text-to-image)

- Generative Visual Manipulation on the Natural Image Manifold [[Project]](http://www.eecs.berkeley.edu/~junyanz/projects/gvm/) [[Youtube]](https://youtu.be/9c4z6YsBGQ0) [[Paper]](https://arxiv.org/abs/1609.03552) [[Code]](https://github.com/junyanz/iGAN)

- Global-to-Local Generative Model for 3D Shapes [[Project]](http://vcc.szu.edu.cn/research/2018/G2L)[[Code]](https://github.com/Hao-HUST/G2LGAN)

- GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks [[arXiv]](https://arxiv.org/abs/1710.00962)

- GP-GAN: Towards Realistic High-Resolution Image Blending [[arXiv]](https://arxiv.org/abs/1703.07195)

- Guiding InfoGAN with Semi-Supervision [[arXiv]](https://arxiv.org/abs/1707.04487)

- How to Fool Radiologists with Generative Adversarial Networks? A Visual Turing Test for Lung Cancer Diagnosis [[arXiv]](https://arxiv.org/abs/1710.09762)

- Hierarchical Detail Enhancing Mesh-Based Shape Generation with 3D Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1709.07581)

- High-Quality Face Image SR Using Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.00737)

- High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks [[arXiv]](https://arxiv.org/abs/1710.10182)

- Image De-raining Using a Conditional Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1701.05957)

- Image Generation and Editing with Variational Info Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1701.04568)

- Image-to-Image Translation with Conditional Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.07004) [[Code]](https://github.com/phillipi/pix2pix)

- Improved Adversarial Systems for 3D Object Generation and Reconstruction [[arXiv]](https://arxiv.org/abs/1707.09557) [[Code]](https://github.com/EdwardSmith1884/3D-IWGAN)

- Improving Heterogeneous Face Recognition with Conditional Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.02848)

- Improving image generative models with human interactions [[arXiv]](https://arxiv.org/abs/1709.10459)

- Imitating Driver Behavior with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1701.06699)

- Interactive 3D Modeling with a Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1706.05170)

- Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.02255)

- Invertible Conditional GANs for image editing [[arXiv]](https://arxiv.org/abs/1611.06355) [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_8.pdf)

- Joint Discriminative and Generative Learning for Person Re-identification [[Project]](http://zdzheng.xyz/DG-Net/) [[Paper]](https://arxiv.org/abs/1904.07223) [[YouTube]](https://www.youtube.com/watch?v=ubCrEAIpQs4) [[Bilibili]](https://www.bilibili.com/video/av51439240) [[Poster]](http://zdzheng.xyz/images/DGNet_poster.pdf) [[Code]](https://github.com/NVlabs/DG-Net)

- Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Images [[arXiv]](https://arxiv.org/abs/1709.01993)

- Learning a Driving Simulator [[arXiv]](https://arxiv.org/abs/1608.01230)

- Learning a Generative Adversarial Network for High Resolution Artwork Synthesis [[arXiv]](https://arxiv.org/abs/1708.09533)

- Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling [[arXiv]](https://arxiv.org/abs/1610.07584)

- Learning from Simulated and Unsupervised Images through Adversarial Training [[arXiv]](https://arxiv.org/abs/1612.07828)

- Learning to Discover Cross-Domain Relations with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.05192)

- Learning to Generate Chairs with Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1705.10413)

- Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.07592)

- Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss [[arXiv]](https://arxiv.org/abs/1708.00961)

- MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification [[arXiv]](https://arxiv.org/abs/1612.08879)

- Megapixel Size Image Creation using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1706.00082)

- Microscopy Cell Segmentation via Adversarial Neural Networks [[arXiv]](https://arxiv.org/abs/1709.05860)

- MoCoGAN: Decomposing Motion and Content for Video Generation [[arXiv]](https://arxiv.org/abs/1707.04993)

- Multi-view Generative Adversarial Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_13.pdf)

- Neural Photo Editing with Introspective Adversarial Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_15.pdf) [[arXiv]](https://arxiv.org/abs/1609.07093)

- Neural Stain-Style Transfer Learning using GAN for Histopathological Images [[arXiv]](https://arxiv.org/abs/1710.08543)

- Outline Colorization through Tandem Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.08834)

- Perceptual Adversarial Networks for Image-to-Image Transformation [[arXiv]](https://arxiv.org/abs/1706.09138)

- Perceptual Generative Adversarial Networks for Small Object Detection [[arXiv]](https://arxiv.org/abs/1706.05274)

- Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1609.04802)

- Pose Guided Person Image Generation [[arXiv]](https://arxiv.org/abs/1705.09368)

- Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1604.04382)

- Recurrent Topic-Transition GAN for Visual Paragraph Generation [[arXiv]](https://arxiv.org/abs/1703.07022)

- RenderGAN: Generating Realistic Labeled Data [[arXiv]](https://arxiv.org/abs/1611.01331)

- Representation Learning and Adversarial Generation of 3D Point Clouds [[arXiv]](https://arxiv.org/abs/1707.02392)

- Retinal Vasculature Segmentation Using Local Saliency Maps and Generative Adversarial Networks For Image Super Resolution [[arXiv]](https://arxiv.org/abs/1710.04783)

- Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1706.09318)

- SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.08788)

- SalGAN: Visual Saliency Prediction with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1701.01081v2)

- SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation [[arXiv]](https://arxiv.org/abs/1706.01805)

- SeGAN: Segmenting and Generating the Invisible [[arXiv]](https://arxiv.org/abs/1703.10239)

- Semantic Image Inpainting with Deep Generative Models [[arXiv]](https://arxiv.org/abs/1607.07539)

- EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning [[arXiv]](https://arxiv.org/abs/1901.00212) [[Code]](https://github.com/knazeri/edge-connect)

- Semantic Image Synthesis via Adversarial Learning [[arXiv]](https://arxiv.org/abs/1707.06873)

- Semantic Segmentation using Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.08408)

- Semantically Decomposing the Latent Spaces of Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1705.07904)

- Semi-Latent GAN: Learning to generate and modify facial images from attributes [[arXiv]](https://arxiv.org/abs/1704.02166)

- Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.06430)

- Sharpness-aware Low dose CT denoising using conditional generative adversarial network [[arXiv]](https://arxiv.org/abs/1708.06453)

- Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1708.09105)

- SingleGAN: Image-to-Image Translation by a Single-Generator Network using Multiple Generative Adversarial Learning [[arXiv]](https://arxiv.org/abs/1810.04991) [[Code]](https://github.com/Xiaoming-Yu/SingleGAN)

- Socially-compliant Navigation through Raw Depth Inputs with Generative Adversarial Imitation Learning [[arXiv]](https://arxiv.org/abs/1710.02543)

- StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1612.03242)

- StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1710.10916)

- Style Transfer for Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN [[arXiv]](https://arxiv.org/abs/1706.03319)

- Supervised Adversarial Networks for Image Saliency Detection [[arXiv]](https://arxiv.org/abs/1704.07242)

- Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs) [[arXiv]](https://arxiv.org/abs/1707.09747)

- Synthesizing Filamentary Structured Images with GANs [[arXiv]](https://arxiv.org/abs/1706.02185)

- Synthetic Iris Presentation Attack using iDCGAN [[arXiv]](https://arxiv.org/abs/1710.10565)

- Synthetic Medical Images from Dual Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.01872)

- TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1703.06412)

- Temporal Generative Adversarial Nets with Singular Value Clipping [[arXiv]](https://arxiv.org/abs/1611.06624)

- TextureGAN: Controlling Deep Image Synthesis with Texture Patches [[arXiv]](https://arxiv.org/abs/1706.02823)

- Texture Synthesis with Spatial Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.08207v3) [[Code]](https://github.com/ubergmann/spatial_gan)

- Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language [[arXiv]](https://arxiv.org/abs/1810.11919) [[Code]](https://github.com/woozzu/tagan)

- The Conditional Analogy GAN: Swapping Fashion Articles on People Images [[arXiv]](https://arxiv.org/abs/1709.04695)

- Towards Adversarial Retinal Image Synthesis [[arXiv]](https://arxiv.org/abs/1701.08974) [[Code]](https://github.com/costapt/vess2ret) [[Demo]](http://vess2ret.inesctec.pt/retina)

- Towards Diverse and Natural Image Descriptions via a Conditional GAN [[arXiv]](https://arxiv.org/abs/1703.06029)

- Towards the Automatic Anime Characters Creation with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1708.05509)

- UGAN: Enhancing Underwater Imagery using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1801.04011)

- Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro [[arXiv]](https://arxiv.org/abs/1701.07717)[[Code]](https://github.com/layumi/Person-reID_GAN)

- Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.10593)

- Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1511.06390)

- Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery [[arXiv]](https://arxiv.org/abs/1703.05921)

- Unsupervised Cross-Domain Image Generation [[arXiv]](https://arxiv.org/abs/1611.02200)

- Unsupervised Diverse Colorization via Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1702.06674)

- Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1612.05424)

- Unsupervised Visual Attribute Transfer with Reconfigurable Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.09798)

- VIGAN: Missing View Imputation with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1708.06724)

- WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images [[arXiv]](https://arxiv.org/abs/1702.07392)

- Weakly Supervised Generative Adversarial Networks for 3D Reconstruction [[arXiv]](https://arxiv.org/abs/1705.10904)

- [TomoGAN: Low-Dose X-Ray Tomography with Generative Adversarial Networks] [[scholar]](https://scholar.google.ca/scholar?hl=en&as_sdt=0%2C5&q=TomoGAN%3A+Low-Dose+X-Ray+Tomography+with+Generative+Adversarial+Networks&btnG=) [[arXiv]](https://arxiv.org/abs/1902.07582) 

## Applied Other

- Adversarial Generation of Natural Language [[arXiv]](https://arxiv.org/abs/1705.10929)

- Adversarial Ranking for Language Generation [[arXiv]](https://arxiv.org/abs/1705.11001)

- Adversarial Training Methods for Semi-Supervised Text Classification [[arXiv]](https://arxiv.org/abs/1605.07725) [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_12.pdf)

- A Generative Model for Volume Rendering [[arXiv]](A Generative Model for Volume Rendering)

- ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? [[arXiv]](https://arxiv.org/abs/1708.08227)

- Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN [[arXiv]](https://arxiv.org/abs/1702.05983)

- Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.06490)

- Language Generation with Recurrent Generative Adversarial Networks without Pre-training [[arXiv]](https://arxiv.org/abs/1706.01399)

- Learning to Protect Communications with Adversarial Neural Cryptography [[arXiv]](https://arxiv.org/abs/1610.06918) [[Blog]](https://blog.acolyer.org/2017/02/10/learning-to-protect-communications-with-adversarial-neural-cryptography/)

- Long Text Generation via Adversarial Training with Leaked Information [[arXiv]](https://arxiv.org/abs/1709.08624)

- MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation using 1D and 2D Conditions [[arXiv]](https://arxiv.org/abs/1703.10847)

- MuseGAN: Symbolic-domain Music Generation and Accompaniment with Multi-track Sequential Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.06298)

- Reconstruction of three-dimensional porous media using generative adversarial neural networks [[arXiv]](https://arxiv.org/abs/1704.03225) [[Code]](https://github.com/LukasMosser/PorousMediaGan)

- SEGAN: Speech Enhancement Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1703.09452)

- Semi-supervised Learning of Compact Document Representations with Deep Networks [[Paper]](http://www.cs.nyu.edu/~ranzato/publications/ranzato-icml08.pdf)

- SSGAN: Secure Steganography Based on Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.01613)

- Steganographic Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.05502)

- Towards Grounding Conceptual Spaces in Neural Representations [[arXiv]](https://arxiv.org/abs/1706.04825)

## Humor

- Stopping GAN Violence: Generative Unadversarial Networks [[arXiv]](https://arxiv.org/abs/1703.02528)