目录

• 框架
  • tf-gan
• 基本原理
  • 度量方法
  • basic gan
  • gan landscape
  • gan with the wind
  • gan推导
  • 对抗样本含义
  • gan剪枝
• cv
  • ls-gan
  • wgan
  • lapgan
  • infogan & improvedgan
  • dcgan
  • BigGAN+BigGAN-deep+BigBiGAN
  • TreeGAN
  • stackGAN
  • cycleGAN
  • deblurGAN
  • VQ-VAE
• nlp
  • seqgan
• 搜索与推荐
  • irgan
  • GAN-CDQN
  • rsgan
• 多模态
  • txt2img
• automl
  • autoGAN
• audio
  • gan-tts

框架

tf-gan

https://daiwk.github.io/posts/platform-tf-gan.html

基本原理

度量方法

学习GAN模型量化评价，先从掌握FID开始吧

basic gan

https://daiwk.github.io/posts/image-gan.html

gan landscape

https://daiwk.github.io/posts/cv-gan-overview.html

gan with the wind

https://daiwk.github.io/posts/cv-gan-with-the-wind.html

gan推导

https://daiwk.github.io/posts/cv-gan-theories.html

对抗样本含义

你真的懂对抗样本吗？一文重新思考对抗样本背后的含义

gan剪枝

https://daiwk.github.io/posts/cv-gan-pruning.html

cv

ls-gan

https://daiwk.github.io/posts/image-lsgan.html

wgan

https://daiwk.github.io/posts/image-wgan.html

lapgan

https://daiwk.github.io/posts/image-lapgan.html

infogan & improvedgan

https://daiwk.github.io/posts/image-infogan-improvedgan.html

dcgan

https://daiwk.github.io/posts/image-dcgan.html

BigGAN+BigGAN-deep+BigBiGAN

https://daiwk.github.io/posts/cv-biggan.html

TreeGAN

https://daiwk.github.io/posts/nlp-treegan.html

stackGAN

https://daiwk.github.io/posts/cv-stackgan.html

cycleGAN

https://daiwk.github.io/posts/cv-cyclegan.html

deblurGAN

https://daiwk.github.io/posts/cv-deblurgan.html

VQ-VAE

https://daiwk.github.io/posts/cv-vq-vae.html

nlp

seqgan

https://daiwk.github.io/posts/rl-seqgan.html

搜索与推荐

irgan

https://daiwk.github.io/posts/rl-irgan.html

GAN-CDQN

https://daiwk.github.io/posts/dl-gan-rl-recommend.html

rsgan

https://daiwk.github.io/posts/dl-rsgan.html

多模态

txt2img

https://daiwk.github.io/posts/cv-gan-txt2img.html

automl

autoGAN

https://daiwk.github.io/posts/cv-autogan.html

audio

gan-tts

https://daiwk.github.io/posts/audio-gan-tts.html

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