StarGAN - Official PyTorch Implementation (CVPR 2018)
-
Updated
Jan 23, 2021 - Python
StarGAN - Official PyTorch Implementation (CVPR 2018)
This is a pytorch implementation of the paper: StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks
full tensorflow implementation of the paper: StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks https://arxiv.org/abs/1806.02169
Fully reproduce the paper of StarGAN-VC. Stable training and Better audio quality .
This repository contains code to replicate results from the ICASSP 2020 paper "StarGAN for Emotional Speech Conversion: Validated by Data Augmentation of End-to-End Emotion Recognition".
MM2018 "Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation"
Implementation of Emo-StarGAN
[CVPR 2021: Oral] In this work, we show that high frequency Fourier spectrum decay discrepancies are not inherent characteristics for existing CNN-based generative models.
From scratch, simple and easy-to-understand Pytorch implementation of various generative adversarial network (GAN): GAN, DCGAN, Conditional GAN (cGAN), WGAN, WGAN-GP, CycleGAN, LSGAN, and StarGAN.
Pytorch implementations of GANs
A PyTorch implementation of StarGAN-VC2.
Implementation of StarGAN in Tensorflow
StarGAN with a triple consistency loss
please smile
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Tensorflow implementation of StarGAN. Feature translation between images using Generative Adversarial Networks (GANs). It allows to modify a physical characteristic such as the hair color.
Add a description, image, and links to the stargan topic page so that developers can more easily learn about it.
To associate your repository with the stargan topic, visit your repo's landing page and select "manage topics."