Skip to content

Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks'', by Reinhard Heckel and Paul Hand

Notifications You must be signed in to change notification settings

wszc-2021/supplement_deep_decoder

 
 

Repository files navigation

Deep Decoder

This repository provides code for reproducing the figures in the paper:

``Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks'', by Reinhard Heckel and Paul Hand. Contact: [email protected]

The paper is available online [here].

The deep decoder is a simple image generating deep neural network. The network is untrained, non-convolutional, and under-parameterized, i.e., it generates images from few paramters. The deep decoder enables image compression and solving invere problems:

Installation

The code is written in python and relies on pytorch. The following libraries are required:

  • python 3
  • pytorch
  • numpy
  • skimage
  • matplotlib
  • scikit-image
  • jupyter

The libraries can be installed via:

conda install jupyter

Citation

@article{heckel_deep_2018,
    author    = {Reinhard Heckel and Paul Hand},
    title     = {Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks},
    journal   = {International Conference on Learning Representations},
    year      = {2019}
}

Licence

All files are provided under the terms of the Apache License, Version 2.0.

About

Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks'', by Reinhard Heckel and Paul Hand

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 99.7%
  • Python 0.3%