https://github.com/astorfi/really-awesome-gan
A list of papers on Generative Adversarial (Neural) Networks
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A list of papers on Generative Adversarial (Neural) Networks
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# 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# 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 & GANstowards 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) - 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) - 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) - 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) - 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 PixelLevel 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)
Owner
- Name: Sina Torfi
- Login: astorfi
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PhD & Developer working on Deep Learning, Computer Vision & NLP


