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GAN变种及应用汇总

网络变种

1、PyTorch-GAN

https://github.com/eriklindernoren/PyTorch-GAN

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Table of Contents
Installation
Implementations
Auxiliary Classifier GAN
Adversarial Autoencoder
BEGAN
BicycleGAN
Boundary-Seeking GAN
Cluster GAN
Conditional GAN
Context-Conditional GAN
Context Encoder
Coupled GAN
CycleGAN
Deep Convolutional GAN
DiscoGAN
DRAGAN
DualGAN
Energy-Based GAN
Enhanced Super-Resolution GAN
GAN
InfoGAN
Least Squares GAN
MUNIT
Pix2Pix
PixelDA
Relativistic GAN
Semi-Supervised GAN
Softmax GAN
StarGAN
Super-Resolution GAN
UNIT
Wasserstein GAN
Wasserstein GAN GP
Wasserstein GAN DIV

应用

风格迁移

1、pystiche

https://github.com/pmeier/pystiche

Framework for Neural Style Transfer (NST) built upon PyTorch

2、GMA_CI_2019_ssim_content_loss

https://github.com/pmeier/GMA_CI_2019_ssim_content_loss

Content representation for Neural Style Transfer Algorithms based on Structural Similarity

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本文标题:GAN变种及应用汇总

文章作者:

发布时间:2021年01月07日 - 16:58

最后更新:2021年01月08日 - 11:43

原始链接:https://yangsuhui.github.io/p/eac6.html

许可协议: 署名-非商业性使用-禁止演绎 4.0 国际 转载请保留原文链接及作者。

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