Semi-supervised learning of object categories from paired local features

Abstract

This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a large amount of unlabeled data as well as a small amount of labeled data to boost classification performance. Our approach proposes to formulate the problem of matching two images as… (More)
DOI: 10.1145/1386352.1386386

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