Image similarity resources – Deep Learning Garden

This page provides resources about image similarity using deep learning, Siamese network, one-shot learning. There are several ways to compute image similarity with deep learning. One can either train an end to end deep model which learns similarity between images, or use the Deep model as a feature extractor and then use a standard similarity metric (Dot product, L2 distance etc.) It depends on the problem domain at hand. For example, if these are natural images with scenes/objects, one can use a pre-trained deep model (say, a GoogleNet model trained on ImageNet or maybe Natural scene images (like, say Places-205) and then extract features from one of the last few layers (either fc6 or fc7).