Learning to Discover Novel Visual Categories via Deep Transfer Clustering
Learning to Discover Novel Visual Categories via Deep Transfer Clustering
We consider the problem of discovering novel object categories in an image collection. While these images are unlabelled, we also assume prior knowledge of related but different image classes. We use such prior knowledge to reduce the ambiguity of clustering, and improve the quality of the newly discovered classes. Our …