Novel Visual Category Discovery with Dual Ranking Statistics and Mutual Knowledge Distillation

In this paper, we tackle the problem of novel visual category discovery, i.e., grouping unlabelled images from new classes into different semantic partitions by leveraging a labelled dataset that contains images from other different but relevant categories.