Collection of generative models in Pytorch version.

Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset

My implementation of various GAN (generative adversarial networks) architectures like vanilla GAN (Goodfellow et al.), cGAN (Mirza et al.), DCGAN (Radford et al.), etc.

[NeurIPS 2022, T-PAMI 2023] Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models

Tensorflow implementation for Conditional Convolutional Adversarial Networks.

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.

Official PyTorch implementation of Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation (ICLR 2019)

[MICCAI'21] [Tensorflow] Retinal Vessel Segmentation using a Novel Multi-scale Generative Adversarial Network

The implementation of 'Image synthesis via semantic composition', ICCV2021.

Text to Image Synthesis using Generative Adversarial Networks

Generative Adversarial Networks in TensorFlow 2.0

PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)

🎨 Anime generation with GANs.

GAN models with Anime.

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

Few-shot image translation method working on unstructured environments. ECCV 2022

Conditional Sequence Generative Adversarial Network trained with policy gradient, Implementation in Tensorflow

Code implementation for paper that "ACSCS: Crowd Counting via Adversarial Cross-Scale Consistency Pursuit"; This is method of Crowd counting by conditional generation adversarial networks

Code for the paper: Multi-Label Clinical Time-Series Generation via Conditional GAN (IEEE TKDE)