{"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/an-all-in-one-convolutional-neural-network","title":"An All-In-One Convolutional Neural Network for Face Analysis","arxiv_id":"1611.00851","date":"2016-11-03","proceeding":null,"authors":["Rajeev Ranjan","Swami Sankaranarayanan","Carlos D. Castillo","Rama Chellappa"],"abstract":"We present a multi-purpose algorithm for simultaneous face detection, face\nalignment, pose estimation, gender recognition, smile detection, age estimation\nand face recognition using a single deep convolutional neural network (CNN).\nThe proposed method employs a multi-task learning framework that regularizes\nthe shared parameters of CNN and builds a synergy among different domains and\ntasks. Extensive experiments show that the network has a better understanding\nof face and achieves state-of-the-art result for most of these tasks.","url_abs":"http://arxiv.org/abs/1611.00851v1","url_pdf":"http://arxiv.org/pdf/1611.00851v1.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":"an-all-in-one-convolutional-neural-network","repo_url":"https://github.com/senguptaumd/SfSNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"age-estimation","task_name":"Age Estimation"},{"task_slug":"all","task_name":"All"},{"task_slug":"face-alignment","task_name":"Face Alignment"},{"task_slug":"face-detection","task_name":"Face Detection"},{"task_slug":"face-recognition","task_name":"Face Recognition"},{"task_slug":"face-verification","task_name":"Face Verification"},{"task_slug":"multi-task-learning","task_name":"Multi-Task Learning"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/face-verification-on-ijb-a","task":"Face Verification","dataset":"IJB-A","model":"All-in-one CNN","rank_in_archive_order":10,"of":17,"metrics":{"TAR @ FAR=0.01":"92.20%"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1611.00851","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}