[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.

pyTorch implementation of Spectral Normalization for Generative Adversarial Networks

PyTorch implementation of DCGAN, WGAN-GP and SNGAN.

Implementation of some different variants of GANs by tensorflow, Train the GAN in Google Cloud Colab, DCGAN, WGAN, WGAN-GP, LSGAN, SNGAN, RSGAN, RaSGAN, BEGAN, ACGAN, PGGAN, pix2pix, BigGAN

Spectral Normalization for Keras Dense and Convolution Layers

An unofficial Pytorch implementation of SNGAN, achieving IS of 8.21 and FID of 14.21 on CIFAR-10.

Simply implement the paper: cGANs with Projection Discriminator by TensorFlow

A implement of spectral normalization GAN for tensorflow version

Unofficial implementation of SNGAN in PyTorch

Spectral Normalization and Projection Discriminator

Official PyTorch repository for Quaternion Generative Adversarial Networks.

Tutorial introduction slides to GANs. Code implementations and links of relevant papers.

Tensorflow implemention of various GAN.

This Repository Contains Solution to the Assignments of the Generative Adversarial Networks (GANs) Specialization from deeplearning.ai on Coursera Taught by Sharon Zhou, Eda Zhou, Eric Zelikman

This repository contains an implementation of a DCGAN and a SNGAN for image generation. More precisely, it is dedicated to artificial image synthesis in the context of medical imaging data.

A Pytorch implementation of "Spectral Normalization for Generative Adversarial Networks"

A Tensorflow 2 implementation of SNGAN and Projection Discriminator

Applying DCGAN on pokemon images to uncover potential AI-created cool pokemons

A simple SNGAN toy example to overfit on few solid colors.

Implementations of Generative Adversarial Networks and AutoEncoders in Pytorch