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Super Resolution using perceptual loss

The aim is to test using perceptual loss for a Super Resolution model

The Network

The Results

Pics can be seen in the Jupyter notebook

Overall the results are pretty good for such a small amount of data and training. Also optimization of the model (loss function mostly) should improve the results if trained on full imagenet set etc

Next steps to try

  • Using Imagenet training set
  • Using Resnet50 as the basic model for feature extraction

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Example of 8x Super Resolution using Up Sampling CNN and VGG 16 Keras/TensorFlow

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  • Jupyter Notebook 99.8%
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