Collection of generative models in Tensorflow
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Updated
Jul 21, 2018 - Python
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Collection of generative models in Tensorflow
Collection of generative models in Pytorch version.
All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN
[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.
Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset
Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch
Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
cGAN-based Multi Organ Nuclei Segmentation
Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.
Pytorch implementation of pix2pix for various datasets.
Implementation of Conditional Generative Adversarial Networks in PyTorch
MATLAB implementations of Generative Adversarial Networks -- from GAN to Pixel2Pixel, CycleGAN
A Conditional Generative Adverserial Network (cGAN) was adapted for the task of source de-noising of noisy voice auditory images. The base architecture is adapted from Pix2Pix.
cGAN-based Manga Colorization Using a Single Training Image.
Generating Elevation Surface from a Single RGB Remotely Sensed Image Using Deep Learning
GANs Implementations in Keras
This repository is as a research project in the field of super resolution. It uses RDN as the generator and spectral norm is used in discriminator.
Channel Estimation for One-Bit Multiuser Massive MIMO Using Conditional GAN
Official Pytorch implementation of "DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network" (CVPR'21)
mxnet implement for Conditional Wasserstein GAN
Spectral Normalization and Projection Discriminator
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