There are 2 repositories under infogan topic.
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
learn code with tensorflow
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Simple Implementation of many GAN models with PyTorch.
PyTorch Implementation of InfoGAN
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
implement infoGAN using pytorch
InfoGAN inspired neural network trained on zap50k images (using Tensorflow + tf-slim). Intermediate layers of the discriminator network are used to do image similarity.
Pytorch implementations of generative models: VQVAE2, AIR, DRAW, InfoGAN, DCGAN, SSVAE
Repository for implementation of generative models with Tensorflow 1.x
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
Performance comparison of ACGAN, BEGAN, CGAN, DRAGAN, EBGAN, GAN, infoGAN, LSGAN, VAE, WGAN, WGAN_GP on cifar-10
Generative Adversarial Networks with TensorFlow2, Keras and Python (Jupyter Notebooks Implementations)
PyTorch implemented generative models for CelebA dataset: DCGAN, LSGAN, WGAN, WGANGP, InfoGAN, BEGAN, VAE, VAEGAN
GANs Implementations in Keras
Playing with MNIST. Machine Learning. Generative Models.
Beginner's Guide to building GAN from scratch with Tensorflow and Keras
The GAN Book: Train stable Generative Adversarial Networks using TensorFlow2, Keras and Python.
Repository for my research on generative modelling of cell images
Tutorial introduction slides to GANs. Code implementations and links of relevant papers.
Keras implementation of InfoGAN (work in progress)
Implement multiple gan including vanilla_gan, dcgan, cgan, infogan and wgan with tensorflow and dataset including mnist.
PyTorch implementations of Generative Adversarial Network series
Quick Tensorflow 2.0 implementation of InfoGAN trained on MNIST.
GAN / DCGAN / InfoGAN / BEGAN ...