Popular GitHub Repositories for Infogan

Collection of generative models in Tensorflow

Collection of generative models in Pytorch version.

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

Simple Implementation of many GAN models with PyTorch.

Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.

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

:dolls: InfoGAN: Interpretable Representation Learning

InfoGAN inspired neural network trained on zap50k images (using Tensorflow + tf-slim). Intermediate layers of the discriminator network are used to do image similarity.

Generative models (GAN, VAE, Diffusion Models, Autoregressive Models) implemented with Pytorch, Pytorch_lightning and hydra.

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

Simple implementation of Least Squares Generative Adversarial Networks

[ICML 2020] InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs

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)

Official PyTorch implementation on ID-GAN: High-Fidelity Synthesis with Disentangled Representation by Lee et al., 2020.

A tensorflow implementation of informative generative adversarial network (InfoGAN ) to one dimensional ( 1D ) time series data with a supervised loss function. So it's called semisupervised Info GAN.

Semi-supervised InfoGAN

GANs Implementations in Keras

Playing with MNIST. Machine Learning. Generative Models.

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