There are 5 repositories under conditional-gan topic.
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.
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.
Text to Image Synthesis using Generative Adversarial Networks
Generative Adversarial Networks in TensorFlow 2.0
🎨 Anime generation with GANs.
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
Pytorch implementation of Conditional-GAN (CGAN)
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
Conditioning of three-dimensional geological and pore scale generative adversarial networks
This project uses a conditional generative adversarial network (cGAN) named Pix2Pix for the Image to image translation task.
Image to Image Translation using Conditional GANs (Pix2Pix) implemented using Tensorflow 2.0
Code for the paper: Multi-Label Clinical Time-Series Generation via Conditional GAN (IEEE TKDE)
Implementation of paper everybody dance now for Deep learning course project
Deep learning works for ADLxMLDS (CSIE 5431) in NTU
Resolving semantic confusions for improved zero-shot detection (BMVC 2022)
An unofficial PyTorch implementation of SNGAN (ICLR 2018) and cGANs with projection discriminator (ICLR 2018)
Unofficial implementation of "Crowd Counting via Adversarial Cross-Scale Consistency Pursuit" with pytorch - CVPR 2018
Conversion of sketches to photos using GANs.