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 dis...

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Bibliographic Details
Main Authors: Han, K, Vedaldi, A, Zisserman, A
Format: Conference item
Language:English
Published: IEEE 2020