[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.
-
Updated
Aug 7, 2022 - Python
[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.
pyTorch implementation of Spectral Normalization for Generative Adversarial Networks
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
Spectral Normalization and Projection Discriminator
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
Official PyTorch repository for Quaternion Generative Adversarial Networks.
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
Add a description, image, and links to the sngan topic page so that developers can more easily learn about it.
To associate your repository with the sngan topic, visit your repo's landing page and select "manage topics."