{"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/face-attention-network-an-effective-face","title":"Face Attention Network: An Effective Face Detector for the Occluded Faces","arxiv_id":"1711.07246","date":"2017-11-20","proceeding":null,"authors":["Jianfeng Wang","Ye Yuan","Gang Yu"],"abstract":"The performance of face detection has been largely improved with the\ndevelopment of convolutional neural network. However, the occlusion issue due\nto mask and sunglasses, is still a challenging problem. The improvement on the\nrecall of these occluded cases usually brings the risk of high false positives.\nIn this paper, we present a novel face detector called Face Attention Network\n(FAN), which can significantly improve the recall of the face detection problem\nin the occluded case without compromising the speed. More specifically, we\npropose a new anchor-level attention, which will highlight the features from\nthe face region. Integrated with our anchor assign strategy and data\naugmentation techniques, we obtain state-of-art results on public face\ndetection benchmarks like WiderFace and MAFA. The code will be released for\nreproduction.","url_abs":"http://arxiv.org/abs/1711.07246v2","url_pdf":"http://arxiv.org/pdf/1711.07246v2.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":"face-attention-network-an-effective-face","repo_url":"https://github.com/rainofmine/Face_Attention_Network","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"face-detection","task_name":"Face Detection"},{"task_slug":"occluded-face-detection","task_name":"Occluded Face Detection"}],"methods":[{"method_slug":null,"method_name":"Trust Wallet"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/occluded-face-detection-on-mafa","task":"Occluded Face Detection","dataset":"MAFA","model":"FAN","rank_in_archive_order":1,"of":2,"metrics":{"MAP":"88.3%"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1711.07246","atlas_url":"https://app.syntology.ai/?focus=1711.07246","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}