Reviews: Generating Images with Perceptual Similarity Metrics based on Deep Networks

I think the most important contribution of the manuscript is to describe a method that substantially improves image reconstruction from compressed deep network representations (e.g. In that regard I would have liked an analysis of the compression rate for the reconstructions from the different feature spaces. In particular because the difference in quality between layer conv5 and fc6 doesn't seem too large, whereas there is a 10-fold reduction in dimensionality ((13 x 13 x 256 43k vs. to 4k) in the feature representation. One factor that should definitely be discussed in the paper is that it appears as if the adversarial prior enforces to use image data from the training set in the reconstruction. This is not necessarily a problem in terms of image compression, but is an important factor: a careful choice of training data might be important depending on what type of images one wants to compress.