Category learning neural networks

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a clustering of images into a plurality of semantic categories. In one aspect, a method comprises: training a categorization neural network, comprising, at each of a plurality of iterations: processing an image depicting an object using the categorization neural network to generate (i) a current prediction for whether the image depicts an object or a background region, and (ii) a current embedding of the image; determining a plurality of current cluster centers based on the current values of the categorization neural network parameters, wherein each cluster center represents a respective semantic category; and determining a gradient of an objective function that includes a classification loss and a clustering loss, wherein the clustering loss depends on a similarity between the current embedding of the image and the current cluster centers.