{"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/data-specific-adaptive-threshold-for-face","title":"Data-specific Adaptive Threshold for Face Recognition and Authentication","arxiv_id":"1810.11160","date":"2018-10-26","proceeding":null,"authors":["Hsin-Rung Chou","Jia-Hong Lee","Yi-Ming Chan","Chu-Song Chen"],"abstract":"Many face recognition systems boost the performance using deep learning\nmodels, but only a few researches go into the mechanisms for dealing with\nonline registration. Although we can obtain discriminative facial features\nthrough the state-of-the-art deep model training, how to decide the best\nthreshold for practical use remains a challenge. We develop a technique of\nadaptive threshold mechanism to improve the recognition accuracy. We also\ndesign a face recognition system along with the registering procedure to handle\nonline registration. Furthermore, we introduce a new evaluation protocol to\nbetter evaluate the performance of an algorithm for real-world scenarios. Under\nour proposed protocol, our method can achieve a 22\\% accuracy improvement on\nthe LFW dataset.","url_abs":"http://arxiv.org/abs/1810.11160v1","url_pdf":"http://arxiv.org/pdf/1810.11160v1.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":"data-specific-adaptive-threshold-for-face","repo_url":"https://github.com/ivclab/Online-Face-Recognition-and-Authentication","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"data-specific-adaptive-threshold-for-face","repo_url":"https://github.com/Faceplugin-ltd/FaceRecognition-Android","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"face-recognition","task_name":"Face Recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/face-recognition-on-adience-online-open-set","task":"Face Recognition","dataset":"Adience (Online Open Set)","model":"FaceNet+Adaptive Threshold","rank_in_archive_order":1,"of":2,"metrics":{"Average Accuracy (10 times)":"84.3"},"uses_additional_data":true},{"leaderboard":"/sota/face-recognition-on-adience-online-open-set","task":"Face Recognition","dataset":"Adience (Online Open Set)","model":"FaceNet+Fixed Threshold (0.2487)","rank_in_archive_order":2,"of":2,"metrics":{"Average Accuracy (10 times)":"80.6"},"uses_additional_data":true},{"leaderboard":"/sota/face-recognition-on-color-feret-online-open","task":"Face Recognition","dataset":"Color FERET (Online Open Set)","model":"FaceNet+Adaptive Threshold","rank_in_archive_order":1,"of":2,"metrics":{"Average Accuracy (10 times)":"83.79"},"uses_additional_data":true},{"leaderboard":"/sota/face-recognition-on-color-feret-online-open","task":"Face Recognition","dataset":"Color FERET (Online Open Set)","model":"FaceNet+Fixed Threshold (0.3968)","rank_in_archive_order":2,"of":2,"metrics":{"Average Accuracy (10 times)":"80.72"},"uses_additional_data":true},{"leaderboard":"/sota/face-recognition-on-lfw-online-open-set","task":"Face Recognition","dataset":"LFW (Online Open Set)","model":"FaceNet+Adaptive Threshold","rank_in_archive_order":1,"of":2,"metrics":{"Average Accuracy (10 times)":"76.46"},"uses_additional_data":true},{"leaderboard":"/sota/face-recognition-on-lfw-online-open-set","task":"Face Recognition","dataset":"LFW (Online Open Set)","model":"FaceNet+Fixed Threshold (0.3779)","rank_in_archive_order":2,"of":2,"metrics":{"Average Accuracy (10 times)":"53.97"},"uses_additional_data":true}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}