Export Reviews, Discussions, Author Feedback and Meta-Reviews

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This paper described a novel method to train convolutional neural networks (CNNs) in an unsupervised fashion such that the model still learns to be invariant to common transformations. The method proposed by the authors is simple and, some extent, elegant. The idea is to simply train the CNN to distinguish image patches and their transformations from other image patches and their transformations. This approach allows the model to learn to be invariant to common transformation. However, as the authors mention, the method is vulnerable to collisions where distinct image patches -- that the model will try to distinguish -- share the same content.