Reviews: Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions

While the paper is well structured and easy to follow until Section 3.1, there are some open questions on the technical side and the motivation behind the proposed steps. Why is a specific intermediate GMM representation needed instead of letting a neural network do what it is good for: learning good intermediate representations? Especially fixing the derivative filters of the first network seems an unnecessary restriction. The approach has also some similarity to using VLAD/FisherVector features as inputs or the more recently proposed NetVLAD neural network architecture. So what is the difference of the presented approach to the ones mentioned?