Skip to content

A Variational Autoencoder based on the ResNet18-architecture

Notifications You must be signed in to change notification settings

BobZwr/VAE-ResNet18-PyTorch

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 

Repository files navigation

VAE-ResNet18-PyTorch

A Variational Autoencoder based on the ResNet18-architecture, implemented in PyTorch.

Out of the box, it works on 64x64 3-channel input, but can easily be changed to 32x32 and/or n-channel input.

Instead of transposed convolutions, it uses a combination of upsampling and convolutions, as described here:
https://distill.pub/2016/deconv-checkerboard/

The implementation of the encoder is inspired by https://github.com/kuangliu/pytorch-cifar

About

A Variational Autoencoder based on the ResNet18-architecture

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%