Implementation of Unifying Deep Local and Global Features for Image Search
Used small subset of ImageNet - Imagewoof, dataset with 10 classes of dogs.
From paper above it's important to train model in two steps - training global features & training local features.
Global features produce embedding like this:
(Big black points - class centroids)
For training local features used attention, here are few examples of attention maps:
