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Deep image prior

In this repository we provide Jupyter Notebooks to reproduce each figure from the paper:

Deep Image Prior

Dmitry Ulyanov, Andrea Vedaldi, Victor Lempitsky

[paper] [supmat] [project page]

Here we provide hyperparameters and architectures, that were used to generate the figures. Most of them are far from optimal. Do not hesitate to change them and see the effect.

We will expand this README with a list of hyperparameters and options shortly.

Install

Here is the list of libraries you need to install to execute the code:

  • pytorch > 0.2
  • numpy
  • scipy
  • matplotlib
  • scikit-image
  • jupyter

All of them can be installed via conda (anaconda), e.g.

conda install jupyter

Citation

@article{UlyanovVL17,
    author    = {Ulyanov, Dmitry and Vedaldi, Andrea and Lempitsky, Victor},
    title     = {Deep Image Prior},
    journal   = {arXiv:1711.10925},
    year      = {2017}
}

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Image restoration with neural networks but without learning.

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  • Jupyter Notebook 51.4%
  • Python 48.6%