There are 2 repositories under cyclegan-pytorch topic.
A clean and lucid implementation of cycleGAN using PyTorch
Pytorch pipeline for 3D image domain translation using Cycle-Generative-Adversarial-networks, without paired examples.
Official PyTorch implementation of "Artist Style Transfer Via Quadratic Potential"
Review materials for the TWiML Study Group. Contains annotated versions of the original Jupyter noteboooks (look for names like *_jcat.ipynb ), slide decks from weekly Zoom meetups, etc.
Implementation of CycleGAN for Text style transfer with PyTorch.
🌱 SNE-RoadSeg in PyTorch, ECCV 2020 by Rui (Ranger) Fan & Hengli Wang, but now we have improved it.
Pytorch implementation of Self Attentive Adversarial Stain Normalization (SAASN).
Bald-to-Hairy Translation Using CycleGAN
An easy-to-modify and easy-to-follow re-implementation of CycleGAN (cycle-consistent generative adversarial network) in PyTorch
PyTorch implementations of Generative Adversarial Network series
Implement of CycleGAN using pytorch 1.8.
A CycleGAN (generative adversarial network) to try out image generation from synthetic data.
This repository deals with generating 'malign' synthetic samples from 'benign' samples using CycleGAN to mitigate class imbalance and detecting Melanoma using a new balanced skin lesion image dataset.
Implementation of MultiStain-CycleGAN
Using CycleGAN to swap Pokemon types
Basic overview of CycleGAN and its Implementation using Pytorch
We train a CycleGAN model that will generate "realistic" augmented images based on images coming from the Duckietown simulator. This is in an attempt to reducing the reality gap when transitioning from robot training in simulation to real life.
Segmentation of fashion articles from human images
Implemented basic deep learning models using PyTorch
Telegram Bot на aiogram, преобразующий входящие фотографии с помощью Style Transfer или CycleGAN
Breast Cancer H&E classification of Images and Image Generation
Unpaired Image to Image translation using PyTorch
CycleGAN implementation in PyTorch
Solutions for Advanced Image Analysis course assignments, featuring model designs for image summation and generation with MNIST, and style transfer using CycleGAN with MNIST and SVHN datasets.
Scientific Guide AI notebooks is a collection of machine learning and deep learning notebooks prepared by Salem Messoud.
ArtGan for transferring real Images to realism art style.
TNNLS 2024 submission. VerDisGAN and HorDisGAN which control the variation degrees for generated samples
CycleGAN and TwoStylesTransfer realizations
Unofficial Pytorch implementation of CycleGAN for MNIST, USPS, SVHN, MNIST-M, and SyntheticDigits datasets.
A PyTorch implementation using CycleGAN architecture, to read in an image from a set X and transform it so that it looks as if it belongs in set Y .