简介

个人博客： ShawnDong98.github.io

这里是个人学习生成模型时的代码实现。

大部分代码只包含论文复现所需的核心内容，不包含其他内容，并不考虑代码的易用性， 目的是帮助更好地理解论文。

GANs 目录

• GAN：Generative adversarial nets
• DCGAN：Unsupervised representation learning with deep convolutional generative adversarial networks
• WGAN：Wasserstein gan
• VAE：Auto-encoding variational bayes
• CGAN：Conditional Generative Adversarial Nets
• CVAE：Learning structured output representation using deep conditional generative models
• VAE-GAN：Autoencoding beyond pixels using a learned similarity metric
• WGAN-GP：Improved training of wasserstein gans
• AdaIN：Arbitrary style transfer in real-time with adaptive instance normalization
• PGGAN: PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION
• StyleGAN：A Style-Based Generator Architecture for Generative Adversarial Networks
• SAGAN：Self-Attention Generative Adversarial Networks

Reference

• pytorch实现GAN
• PyTorch-GAN/implementations/dcgan
• PyTorch-GAN/implementations/wgan/wgan.py
• Pytorch入门之VAE
• PyTorch-GAN/implementations/cgan/cgan.py
• timbmg/VAE-CVAE-MNIST
• Pytorch-VAE-GAN/blob/master/VAE-GAN.ipynb
• wgan-gp/gan_cifar10.py
• naoto0804/pytorch-AdaIN
• akanimax/pro_gan_pytorch
• rosinality/style-based-gan-pytorch
• heykeetae/Self-Attention-GAN