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Specifically, we propose a novel clustering framework, named structure-enhanced pairwise feature learning (SEPFL), which mixes neighborhood information to adaptively produce pairwise representations for cluster identification. In addition, we design a combined density strategy to select representative pairs, thus ensuring training effectiveness and inference efficiency. The extensive experimental results show that SEPFL achieves better performance than other advanced face clustering techniques.<\/jats:p>","DOI":"10.1007\/s40747-023-00982-z","type":"journal-article","created":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T09:03:03Z","timestamp":1677661383000},"page":"5063-5080","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Structure-enhanced pairwise feature learning for face clustering"],"prefix":"10.1007","volume":"9","author":[{"given":"Shaoying","family":"Li","sequence":"first","affiliation":[]},{"given":"Jie","family":"Li","sequence":"additional","affiliation":[]},{"given":"Bincheng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Bo","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,3,1]]},"reference":[{"issue":"4","key":"982_CR1","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1007\/s10791-008-9066-8","volume":"12","author":"E Amig\u00f3","year":"2009","unstructured":"Amig\u00f3 E, Gonzalo J, Artiles J, Verdejo F (2009) A comparison of extrinsic clustering evaluation metrics based on formal constraints. 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