There are 2 repositories under cyclegan-pytorch topic.
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
A clean and lucid implementation of cycleGAN using PyTorch
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.
Pytorch pipeline for 3D image domain translation using Cycle-Generative-Adversarial-networks, without paired examples.
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.
Bald-to-Hairy Translation Using CycleGAN
Pytorch implementation of Self Attentive Adversarial Stain Normalization (SAASN).
PyTorch implementations of Generative Adversarial Network series
A CycleGAN (generative adversarial network) to try out image generation from synthetic data.
Implement of CycleGAN using pytorch 1.8.
Basic overview of CycleGAN and its Implementation using Pytorch
Using CycleGAN to swap Pokemon types
Segmentation of fashion articles from human images
An easy-to-modify and easy-to-follow re-implementation of CycleGAN (cycle-consistent generative adversarial network) in 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.
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.
Unpaired Image to Image translation using PyTorch
This is a PyTorch implementation of Cycle GAN from Scratch.
CycleGAN and TwoStylesTransfer realizations
Reimplementation of papers on DCGAN and CycleGAN.
Telegram Bot на aiogram, преобразующий входящие фотографии с помощью Style Transfer или CycleGAN
scientific-guide-notebooks is a collection of machine learning and deep learning notebooks
ArtGan for transferring real Images to realism art style.
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 .