Generative Adversarial Networks

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Computer Vision • Generative Models • 48 methods

Generative Adversarial Networks (GANs) are a type of generative model that use two networks, a generator to generate images and a discriminator to discriminate between real and fake, to train a model that approximates the distribution of the data. Below you can find a continuously updating list of GANs.

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Method	Year	Papers
GAN Generative Adversarial Networks	2014	1215
CycleGAN Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks	2017	399
StyleGAN A Style-Based Generator Architecture for Generative Adversarial Networks	2018	290
SAGAN Self-Attention Generative Adversarial Networks	2018	138
Pix2Pix Image-to-Image Translation with Conditional Adversarial Networks	2016	130
BigGAN Large Scale GAN Training for High Fidelity Natural Image Synthesis	2018	103
WGAN Wasserstein GAN	2017	94
DCGAN Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks	2015	81
StyleGAN2 Analyzing and Improving the Image Quality of StyleGAN	2019	54
InfoGAN InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets	2016	35
HiFi-GAN HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis	2020	33
SRGAN Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network	2016	28
LSGAN Least Squares Generative Adversarial Networks	2016	18
ProGAN Progressive Growing of GANs for Improved Quality, Stability, and Variation	2017	16
BiGAN Adversarial Feature Learning	2016	15
SNGAN Spectral Normalization for Generative Adversarial Networks	2018	12
Style Transfer Module Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization	2017	12
WGAN GP Improved Training of Wasserstein GANs	2017	11
BigGAN-deep Large Scale GAN Training for High Fidelity Natural Image Synthesis	2018	11
LOGAN LOGAN: Latent Optimisation for Generative Adversarial Networks	2019	6
Relativistic GAN The relativistic discriminator: a key element missing from standard GAN	2018	6
LAPGAN Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks	2015	5
BigBiGAN Large Scale Adversarial Representation Learning	2019	4
DE-GAN	2000	4
CS-GAN Deep Compressed Sensing	2019	3
TGAN Temporal Generative Adversarial Nets with Singular Value Clipping	2016	3
ACGPN Towards Photo-Realistic Virtual Try-On by Adaptively Generating-Preserving Image Content	2020	3
GFP-GAN Towards Real-World Blind Face Restoration with Generative Facial Prior	2021	3
U-Net GAN A U-Net Based Discriminator for Generative Adversarial Networks	2020	2
MSGAN Multi-source Domain Adaptation for Visual Sentiment Classification	2020	2
LipGAN Towards Automatic Face-to-Face Translation	2020	2
Anycost GAN Anycost GANs for Interactive Image Synthesis and Editing	2021	2
CTAB-GAN Effective and Privacy preserving Tabular Data Synthesizing	2021	2
PresGAN Prescribed Generative Adversarial Networks	2019	1
DVD-GAN Adversarial Video Generation on Complex Datasets	2019	1
TrIVD-GAN Transformation-based Adversarial Video Prediction on Large-Scale Data	2020	1
ALIS Aligning Latent and Image Spaces to Connect the Unconnectable	2021	1
PrivacyNet PrivacyNet: Semi-Adversarial Networks for Multi-attribute Face Privacy	2020	1
PSFR-GAN Progressive Semantic-Aware Style Transformation for Blind Face Restoration	2020	1
StyleMapGAN Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing	2021	1
DU-GAN DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising	2021	1
Attentional Liquid Warping GAN Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis	2020	1
StyleSwin	2000	1
Outlier Generation zGAN: An Outlier-focused Generative Adversarial Network For Realistic Synthetic Data Generation	2024	1

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