Generative Adversarial Networks

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.

METHOD YEAR PAPERS
GAN
2014 1172
CycleGAN
2017 148
WGAN
2017 49
DCGAN
2015 43
StyleGAN
2018 38
SAGAN
2018 35
BigGAN
2018 28
Pix2Pix
2016 27
InfoGAN
2016 17
SRGAN
2016 16
LSGAN
2016 12
StyleGAN2
2019 10
WGAN GP
2017 9
BiGAN
2016 9
SNGAN
2018 7
ProGAN
2017 4
LAPGAN
2015 4
BigBiGAN
2019 3
Relativistic GAN
2018 3
BigGAN-deep
2018 2
CS-GAN
2019 2
PresGAN
2019 1
LOGAN
2019 1
TGAN
2016 1
DVD-GAN
2019 1
TrIVD-GAN
2020 1