Weakly supervised one-shot image segmentation

Abstract

A machine learning model may be trained based on a training set including training images depicting various base objects. Each training images may be associated with a ground-truth segmentation corresponding to one or more pixel-wise labels. The machine learning model may be trained to learn base class prototypes corresponding to segmentations of classes of similar base objects. The machine learning model may be further trained based on a support image depicting a novel object. The support image may be associated with an image-level label corresponding to the novel object. The machine learning model may be trained to learn, based on a base class prototype identified as being similar to the support image, a novel class prototype corresponding to the novel object. The trained machine learning model to may be applied to segment a query image. Related systems and computer program products are also provided.