{"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/git-loss-for-deep-face-recognition","title":"Git Loss for Deep Face Recognition","arxiv_id":"1807.08512","date":"2018-07-23","proceeding":null,"authors":["Alessandro Calefati","Muhammad Kamran Janjua","Shah Nawaz","Ignazio Gallo"],"abstract":"Convolutional Neural Networks (CNNs) have been widely used in computer vision\ntasks, such as face recognition and verification, and have achieved\nstate-of-the-art results due to their ability to capture discriminative deep\nfeatures. Conventionally, CNNs have been trained with softmax as supervision\nsignal to penalize the classification loss. In order to further enhance the\ndiscriminative capability of deep features, we introduce a joint supervision\nsignal, Git loss, which leverages on softmax and center loss functions. The aim\nof our loss function is to minimize the intra-class variations as well as\nmaximize the inter-class distances. Such minimization and maximization of deep\nfeatures are considered ideal for face recognition task. We perform experiments\non two popular face recognition benchmarks datasets and show that our proposed\nloss function achieves maximum separability between deep face features of\ndifferent identities and achieves state-of-the-art accuracy on two major face\nrecognition benchmark datasets: Labeled Faces in the Wild (LFW) and YouTube\nFaces (YTF). However, it should be noted that the major objective of Git loss\nis to achieve maximum separability between deep features of divergent\nidentities.","url_abs":"http://arxiv.org/abs/1807.08512v4","url_pdf":"http://arxiv.org/pdf/1807.08512v4.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":"git-loss-for-deep-face-recognition","repo_url":"https://github.com/kjanjua26/Git-Loss-For-Deep-Face-Recognition","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"face-identification","task_name":"Face Identification"},{"task_slug":"face-recognition","task_name":"Face Recognition"},{"task_slug":"face-verification","task_name":"Face Verification"}],"methods":[{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/face-verification-on-youtube-faces-db","task":"Face Verification","dataset":"YouTube Faces DB","model":"Git Loss","rank_in_archive_order":8,"of":12,"metrics":{"Accuracy":"95.30%"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}