conditional-gan

Collection of generative models in Pytorch version.

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks

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

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Simple Implementation of many GAN models with PyTorch.

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.

In-depth tutorials on deep learning. The first one is about image colorization using GANs (Generative Adversarial Nets).

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.

Generative Adversarial Networks in TensorFlow 2.0

Text to Image Synthesis using Generative Adversarial Networks

🎨 Anime generation with GANs.

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

GAN models with Anime.

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