{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/large-scale-strongly-supervised-ensemble","title":"Large Scale Strongly Supervised Ensemble Metric Learning, with Applications to Face Verification and Retrieval","arxiv_id":"1212.06094","date":"2012-12-25","proceeding":null,"authors":["Chang Huang","Shenghuo Zhu","Kai Yu"],"abstract":"Learning Mahanalobis distance metrics in a high- dimensional feature space is\nvery difficult especially when structural sparsity and low rank are enforced to\nimprove com- putational efficiency in testing phase. This paper addresses both\naspects by an ensemble metric learning approach that consists of sparse block\ndiagonal metric ensembling and join- t metric learning as two consecutive\nsteps. The former step pursues a highly sparse block diagonal metric by\nselecting effective feature groups while the latter one further exploits\ncorrelations between selected feature groups to obtain an accurate and low rank\nmetric. Our algorithm considers all pairwise or triplet constraints generated\nfrom training samples with explicit class labels, and possesses good scala-\nbility with respect to increasing feature dimensionality and growing data\nvolumes. Its applications to face verification and retrieval outperform\nexisting state-of-the-art methods in accuracy while retaining high efficiency.","url_abs":"http://arxiv.org/abs/1212.6094v1","url_pdf":"http://arxiv.org/pdf/1212.6094v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"large-scale-strongly-supervised-ensemble","repo_url":"https://github.com/PaddlePaddle/PaddleClas","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"paddle","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"face-verification","task_name":"Face Verification"},{"task_slug":"metric-learning","task_name":"Metric Learning"},{"task_slug":"retrieval","task_name":"Retrieval"},{"task_slug":null,"task_name":"Triplet"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}