Demo code for reconstructed images from fine-tuned autoencoders
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README.md
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plot_ae_reconstruction.py

README.md

CVPR 2018: What do deep Networks like to See?

Implementation from the CVPR 2018 paper "What do Deep Networks Like to See?".

This is a simple proof of concept that uses a fine-tuned autoencoder on ResNet50 to reconstruct input images.

  1. Download the Torch model from here and store it with the root directory of the repo.
  2. Call
python plot_ae_reconstruction.py -i PATH

where PATH is the path to the input image. 3. An output image should be saved in the root directory of the repo with the reconstruction.

Example:

Original input and its reconstruction using an autoencoder fine-tuned on ResNet 50

For more info, please check out the paper's website.