Generative Adversarial Networks

Published: 09 Oct 2015 Category: deep_learning

Generative Adversarial Networks

Generative Adversarial Nets

Adversarial Feature Learning

Generative Adversarial Networks

Adversarial Examples and Adversarial Training

How to Train a GAN? Tips and tricks to make GANs work

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Learning Interpretable Latent Representations with InfoGAN: A tutorial on implementing InfoGAN in Tensorflow

Coupled Generative Adversarial Networks

Energy-based Generative Adversarial Network

SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

Connecting Generative Adversarial Networks and Actor-Critic Methods

Generative Adversarial Nets from a Density Ratio Estimation Perspective

Unrolled Generative Adversarial Networks

Generative Adversarial Networks as Variational Training of Energy Based Models

Multi-class Generative Adversarial Networks with the L2 Loss Function

Least Squares Generative Adversarial Networks

Inverting The Generator Of A Generative Adversarial Networ


Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks

Associative Adversarial Networks

Temporal Generative Adversarial Nets

Handwriting Profiling using Generative Adversarial Networks

  • intro: Accepted at The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17 Student Abstract and Poster Program)
  • arxiv:

C-RNN-GAN: Continuous recurrent neural networks with adversarial training

Ensembles of Generative Adversarial Networks

Improved generator objectives for GANs

Stacked Generative Adversarial Networks

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

AdaGAN: Boosting Generative Models

Towards Principled Methods for Training Generative Adversarial Networks

Wasserstein GAN

Improved Training of Wasserstein GANs

On the effect of Batch Normalization and Weight Normalization in Generative Adversarial Networks

On the Effects of Batch and Weight Normalization in Generative Adversarial Networks

Controllable Generative Adversarial Network

Generative Adversarial Networks: An Overview

  • intro: Imperial College London & Victoria University of Wellington & University of Montreal & Cortexica Vision Systems Ltd
  • intro: IEEE Signal Processing Magazine Special Issue on Deep Learning for Visual Understanding
  • arxiv:

CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Spectral Normalization for Generative Adversarial Networks

Are GANs Created Equal? A Large-Scale Study

GAGAN: Geometry-Aware Generative Adverserial Networks

CycleGAN: a Master of Steganography

PacGAN: The power of two samples in generative adversarial networks

ComboGAN: Unrestrained Scalability for Image Domain Translation

Decoupled Learning for Conditional Adversarial Networks

No Modes left behind: Capturing the data distribution effectively using GANs

Improving GAN Training via Binarized Representation Entropy (BRE) Regularization

On GANs and GMMs

The Unusual Effectiveness of Averaging in GAN Training

Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis

The GAN Landscape: Losses, Architectures, Regularization, and Normalization

Which Training Methods for GANs do actually Converge?

Convergence Problems with Generative Adversarial Networks (GANs)

Bayesian CycleGAN via Marginalizing Latent Sampling

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

Do GAN Loss Functions Really Matter?

Image-to-Image Translation


Image-to-Image Translation with Conditional Adversarial Networks

Remastering Classic Films in Tensorflow with Pix2Pix

Image-to-Image Translation in Tensorflow

webcam pix2pix

Unsupervised Image-to-Image Translation with Generative Adversarial Networks

Unsupervised Image-to-Image Translation Networks

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

CycleGAN and pix2pix in PyTorch

Perceptual Adversarial Networks for Image-to-Image Transformation

XGAN: Unsupervised Image-to-Image Translation for many-to-many Mappings

In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation

Toward Multimodal Image-to-Image Translation

Face Translation between Images and Videos using Identity-aware CycleGAN

Unsupervised Multi-Domain Image Translation with Domain-Specific Encoders/Decoders

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

On the Effectiveness of Least Squares Generative Adversarial Networks

GANs for Limited Labeled Data

Defending Against Adversarial Examples

Conditional Image-to-Image Translation

XOGAN: One-to-Many Unsupervised Image-to-Image Translation

Unsupervised Attention-guided Image to Image Translation

Exemplar Guided Unsupervised Image-to-Image Translation

Improving Shape Deformation in Unsupervised Image-to-Image Translation

Video-to-Video Synthesis

Segmentation Guided Image-to-Image Translation with Adversarial Networks


Generative Adversarial Networks with Keras

Generative Adversarial Network Demo for Fresh Machine Learning #2

TextGAN: A generative adversarial network for text generation, written in TensorFlow.

cleverhans v0.1: an adversarial machine learning library

Deep Convolutional Variational Autoencoder w/ Adversarial Network

A versatile GAN(generative adversarial network) implementation. Focused on scalability and ease-of-use.

AdaGAN: Boosting Generative Models

TensorFlow-GAN (TFGAN)


Generative Adversial Networks Explained

Generative Adversarial Autoencoders in Theano

An introduction to Generative Adversarial Networks (with code in TensorFlow)

Difficulties training a Generative Adversarial Network

Are Energy-Based GANs any more energy-based than normal GANs?

Generative Adversarial Networks Explained with a Classic Spongebob Squarepants Episode: Plus a Tensorflow tutorial for implementing your own GAN

Deep Learning Research Review Week 1: Generative Adversarial Nets

Stability of Generative Adversarial Networks

Instance Noise: A trick for stabilising GAN training

Generating Fine Art in 300 Lines of Code

Talks / Videos

Generative Adversarial Network visualization


The GAN Zoo

AdversarialNetsPapers: The classical Papers about adversial nets

GAN Timeline