{"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/real-time-deep-hair-matting-on-mobile-devices","title":"Real-time deep hair matting on mobile devices","arxiv_id":"1712.07168","date":"2017-12-19","proceeding":null,"authors":["Alex Levinshtein","Cheng Chang","Edmund Phung","Irina Kezele","Wenzhangzhi Guo","Parham Aarabi"],"abstract":"Augmented reality is an emerging technology in many application domains.\nAmong them is the beauty industry, where live virtual try-on of beauty products\nis of great importance. In this paper, we address the problem of live hair\ncolor augmentation. To achieve this goal, hair needs to be segmented quickly\nand accurately. We show how a modified MobileNet CNN architecture can be used\nto segment the hair in real-time. Instead of training this network using large\namounts of accurate segmentation data, which is difficult to obtain, we use\ncrowd sourced hair segmentation data. While such data is much simpler to\nobtain, the segmentations there are noisy and coarse. Despite this, we show how\nour system can produce accurate and fine-detailed hair mattes, while running at\nover 30 fps on an iPad Pro tablet.","url_abs":"http://arxiv.org/abs/1712.07168v2","url_pdf":"http://arxiv.org/pdf/1712.07168v2.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":"real-time-deep-hair-matting-on-mobile-devices","repo_url":"https://github.com/TureganoJose/ARCproject","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"real-time-deep-hair-matting-on-mobile-devices","repo_url":"https://github.com/jtiger958/hair-segmentation-pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"image-matting","task_name":"Image Matting"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"virtual-try-on","task_name":"Virtual Try-on"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}