I've been learning about SIFT and all the ways its descriptors can be used to do different tasks.
I am particularly interested in the way SIFT can be used for image classification. (e.g. A 2006 paper by Niester & Stewenius relies on SIFT descriptors to build a vocabulary tree).
However, as of 2017, 11 years later, Deep Learning has been replacing the classical approaches in many ways.
What are some alternatives to find feature descriptors for images that, as of 2017, have shown more promising results?