really-awesome-gan

A list of papers and other resources on General 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. Also checkout really-awesome-semantic-segmentation and our COCO-Stuff dataset.

Overview

• Workshops
• Tutorials & Blogs
• Papers
  • Theory & Machine Learning
  • Applied Vision
  • Applied Other
  • Humor
• Videos
• Code

Workshops

• NIPS 2016 Workshop on Adversarial Training [Web] [Blog]

Tutorials & Blogs

• How to Train a GAN? Tips and tricks to make GANs work [Blog]
• NIPS 2016 Tutorial: Generative Adversarial Networks [arXiv]
• On the intuition behind deep learning & GANs — towards a fundamental understanding [Blog]
• OpenAI - Generative Models [Blog]
• SimGANs - a game changer in unsupervised learning, self driving cars, and more [Blog]

Papers

Theory & Machine Learning

• A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models [arXiv]
• A General Retraining Framework for Scalable Adversarial Classification [Paper]
• AdaGAN: Boosting Generative Models [arXiv]
• Adversarial Autoencoders [arXiv]
• Adversarial Discriminative Domain Adaptation [arXiv]
• Adversarial Generator-Encoder Networks [arXiv]
• Adversarial Feature Learning [arXiv] [Code]
• Adversarially Learned Inference [arXiv] [Code]
• An Adversarial Regularisation for Semi-Supervised Training of Structured Output Neural Networks [arXiv]
• Associative Adversarial Networks [arXiv]
• Autoencoding beyond pixels using a learned similarity metric [arXiv]
• BEGAN: Boundary Equilibrium Generative Adversarial Networks [Paper] [arXiv] [Code]
• Boundary-Seeking Generative Adversarial Networks [arXiv] [Code]
• Conditional Generative Adversarial Nets [arXiv] [Code]
• Connecting Generative Adversarial Networks and Actor-Critic Methods [Paper]
• C-RNN-GAN: Continuous recurrent neural networks with adversarial training [arXiv]
• Cooperative Training of Descriptor and Generator Networks [arXiv]
• Coupled Generative Adversarial Networks [arXiv] [Code]
• Deep and Hierarchical Implicit Models [arXiv]
• Energy-based Generative Adversarial Network [arXiv] [Code]
• Explaining and Harnessing Adversarial Examples [arXiv]
• f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization [arXiv] [Code]
• 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]
• Generating images with recurrent adversarial networks [arXiv]
• Generative Adversarial Nets with Labeled Data by Activation Maximization [arXiv]
• Generative Adversarial Networks [arXiv] [Code] [Code]
• Generative Adversarial Networks as Variational Training of Energy Based Models [arXiv]
• Generative Adversarial Parallelization [arXiv] [Code]
• Generative Adversarial Residual Pairwise Networks for One Shot Learning [arXiv]
• Generative Adversarial Structured Networks [Paper]
• Generative Moment Matching Networks [arXiv] [Code]
• Improved Techniques for Training GANs [arXiv] [Code]
• Improved Training of Wasserstein GANs [arXiv] [Code]
• InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets [arXiv] [Code]
• Inverting The Generator Of A Generative Adversarial Network [Paper]
• Learning in Implicit Generative Models [Paper]
• Learning to Discover Cross-Domain Relations with Generative Adversarial Networks [arXiv] [Code]
• Least Squares Generative Adversarial Networks [arXiv] [Code]
• Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities [arXiv]
• LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation [arXiv]
• MAGAN: Margin Adaptation for Generative Adversarial Networks [arXiv] [Code]
• Maximum-Likelihood Augmented Discrete Generative Adversarial Networks [arXiv]
• McGan: Mean and Covariance Feature Matching GAN [arXiv]
• Message Passing Multi-Agent GANs [arXiv]
• Mode Regularized Generative Adversarial Networks [arXiv] [Code]
• Multi-Agent Diverse Generative Adversarial Networks [arXiv]
• On the effect of Batch Normalization and Weight Normalization in Generative Adversarial Networks [arXiv]
• On the Quantitative Analysis of Decoder-Based Generative Models [arXiv]
• SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient [arXiv]
• Simple Black-Box Adversarial Perturbations for Deep Networks [Paper]
• Softmax GAN [arXiv]
• Stacked Generative Adversarial Networks [arXiv]
• Training generative neural networks via Maximum Mean Discrepancy optimization [arXiv]
• Triple Generative Adversarial Nets [arXiv]
• Unrolled Generative Adversarial Networks [arXiv]
• Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks [arXiv] [Code] [Code [Code] [Code] [Code]
• Wasserstein GAN [arXiv] [Code] [Code]

Applied Vision

• 3D Shape Induction from 2D Views of Multiple Objects [arXiv]
• Adversarial Networks for the Detection of Aggressive Prostate Cancer [arXiv]
• Adversarial Training For Sketch Retrieval [arXiv]
• Age Progression / Regression by Conditional Adversarial Autoencoder [arXiv]
• Amortised MAP Inference for Image Super-resolution [arXiv]
• ArtGAN: Artwork Synthesis with Conditional Categorial GANs [arXiv]
• Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis [arXiv]
• Conditional generative adversarial nets for convolutional face generation [Paper]
• Conditional Image Synthesis with Auxiliary Classifier GANs [Paper] [arXiv] [Code]
• Contextual RNN-GANs for Abstract Reasoning Diagram Generation [arXiv]
• CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training [arXiv]
• Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks [arXiv] [Code] [Blog]
• Deep multi-scale video prediction beyond mean square error [arXiv] [Code]
• Deep Unsupervised Representation Learning for Remote Sensing Images [arXiv]
• DualGAN: Unsupervised Dual Learning for Image-to-Image Translation [arXiv] [Code]
• Full Resolution Image Compression with Recurrent Neural Networks [arXiv]
• Generate To Adapt: Aligning Domains using Generative Adversarial Networks [arXiv]
• Generative Adversarial Text to Image Synthesis [arXiv] [Code]
• Generative Visual Manipulation on the Natural Image Manifold [Project] [Youtube] [Paper] [Code]
• GP-GAN: Towards Realistic High-Resolution Image Blending [arXiv]
• Image De-raining Using a Conditional Generative Adversarial Network [arXiv]
• Image Generation and Editing with Variational Info Generative Adversarial Networks [arXiv]
• Image-to-Image Translation with Conditional Adversarial Networks [arXiv] [Code]
• Imitating Driver Behavior with Generative Adversarial Networks [arXiv]
• Invertible Conditional GANs for image editing [arXiv] [Paper]
• Learning a Driving Simulator [arXiv]
• Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling [arXiv]
• Multi-view Generative Adversarial Networks [Paper]
• Neural Photo Editing with Introspective Adversarial Networks [Paper] [arXiv]
• Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network [arXiv]
• Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks [arXiv]
• Recurrent Topic-Transition GAN for Visual Paragraph Generation [arXiv]
• RenderGAN: Generating Realistic Labeled Data [arXiv]
• SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks [arXiv]
• SalGAN: Visual Saliency Prediction with Generative Adversarial Networks [arXiv]
• SeGAN: Segmenting and Generating the Invisible [arXiv]
• Semantic Segmentation using Adversarial Networks [arXiv]
• Semi-Latent GAN: Learning to generate and modify facial images from attributes [arXiv]
• Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks [arXiv]
• StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks [arXiv]
• Supervised Adversarial Networks for Image Saliency Detection [arXiv]
• TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network [arXiv]
• Temporal Generative Adversarial Nets [arXiv]
• Towards Diverse and Natural Image Descriptions via a Conditional GAN [arXiv]
• Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro [arXiv]
• Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks [arXiv]
• Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks [arXiv]
• Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery [arXiv]
• Unsupervised Cross-Domain Image Generation [arXiv]
• WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images [arXiv]

Applied Other

• Adversarial Training Methods for Semi-Supervised Text Classification [arXiv] [Paper]
• Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN [arXiv]
• Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks [arXiv]
• Learning to Protect Communications with Adversarial Neural Cryptography [arXiv] [Blog]
• MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation using 1D and 2D Conditions [arXiv]
• Reconstruction of three-dimensional porous media using generative adversarial neural networks [arXiv] [Code]
• SEGAN: Speech Enhancement Generative Adversarial Network [arXiv]
• Semi-supervised Learning of Compact Document Representations with Deep Networks [Paper]
• Steganographic Generative Adversarial Networks [arXiv]

Humor

• Stopping GAN Violence: Generative Unadversarial Networks [arXiv]

Videos

• Generative Adversarial Networks by Ian Goodfellow [Video]
• Tutorial on Generative Adversarial Networks by Mark Chang [Video]

Code

• Cleverhans: A library for benchmarking vulnerability to adversarial examples [Code] [Blog]
• Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch) [Blog] [Code]
• Generative Models: Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow [Code]