Popular GitHub Repositories for Lsgan

Collection of generative models in Tensorflow

Collection of generative models in Pytorch version.

Awesome Generative Adversarial Networks with tensorflow

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

Reimplementation of GANs

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

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

MATLAB implementations of Generative Adversarial Networks -- from GAN to Pixel2Pixel, CycleGAN

? Variants of GANs most easily implemented as TensorFlow2. GAN, DCGAN, LSGAN, WGAN, WGAN-GP, DRAGAN, ETC...

Torch implementation of various types of GAN (e.g. DCGAN, ALI, Context-encoder, DiscoGAN, CycleGAN, EBGAN, LSGAN)

Chainer implementation of Least Squares GAN (LSGAN)

ProGAN with Standard, WGAN, WGAN-GP, LSGAN, BEGAN, DRAGAN, Conditional GAN, InfoGAN, and Auxiliary Classifier GAN training methods

TensorFlow implementations of Wasserstein GAN with Gradient Penalty (WGAN-GP), Least Squares GAN (LSGAN), GANs with the hinge loss.

Simple implementation of Least Squares Generative Adversarial Networks

PyTorch implemented generative models for CelebA dataset: DCGAN, LSGAN, WGAN, WGANGP, InfoGAN, BEGAN, VAE, VAEGAN

Generative Adversarial Networks with TensorFlow2, Keras and Python (Jupyter Notebooks Implementations)

[CVPR 2021: Oral] In this work, we show that high frequency Fourier spectrum decay discrepancies are not inherent characteristics for existing CNN-based generative models.

Playing with MNIST. Machine Learning. Generative Models.

The GAN Book: Train stable Generative Adversarial Networks using TensorFlow2, Keras and Python.

Anime Character Face Generator (conditional LSGAN)