32 Open source projects that are alternatives of or similar to gan

Playing with MNIST. Machine Learning. Generative Models.

Code for training and evaluation of the model from "Language Generation with Recurrent Generative Adversarial Networks without Pre-training"

Simple Implementation of many GAN models with PyTorch.

Collection of generative models in Pytorch version.

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

Resources and Implementations of Generative Adversarial Nets which are focusing on how to stabilize training process and generate high quality images: DCGAN, WGAN, EBGAN, BEGAN, etc.

A minimal implementaion (less than 150 lines of code with visualization) of DCGAN/WGAN in PyTorch with jupyter notebooks

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

Tensorflow implementation of different GANs and their comparisions

wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch

Chainer implementation of Wasserstein GAN

A Tensorflow implementation of GAN, WGAN and WGAN with gradient penalty.

GAN models with Anime.

でぃーぷらーにんぐを無限にやってディープラーニングでDeepLearningするための実装CheatSheet

Awesome Generative Adversarial Networks with tensorflow

Implementations of (theoretical) generative adversarial networks and comparison without cherry-picking

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

Collection of generative models in Tensorflow

DCGAN LSGAN WGAN-GP DRAGAN Tensorflow 2

Chainer implementation of the Wesserstein GAN

A minimal implementation of Wasserstein GAN

GANs Implementations in Keras

Generative Deep Learning Sessions led by Anugraha Sinha (Machine Learning Tokyo)

Improved Wasserstein GAN (WGAN-GP) application on medical (MRI) images

Applied several Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN and StyleGAN to generate Anime Faces and Handwritten Digits.

Tensorflow Implementation of Paper "Improved Training of Wasserstein GANs"

Repository for implementation of generative models with Tensorflow 1.x

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Pure tensorflow implementation of progressive growing of GANs

Unofficial PyTorch implementation of "Progressive Growing of GANs for Improved Quality, Stability, and Variation".

Simple Pytorch implementations of most used Generative Adversarial Network (GAN) varieties.