{"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/csi-net-unified-human-body-characterization","title":"CSI-Net: Unified Human Body Characterization and Pose Recognition","arxiv_id":"1810.03064","date":"2018-10-07","proceeding":null,"authors":["Fei Wang","Jinsong Han","Shiyuan Zhang","Xu He","Dong Huang"],"abstract":"We build CSI-Net, a unified Deep Neural Network~(DNN), to learn the\nrepresentation of WiFi signals. Using CSI-Net, we jointly solved two body\ncharacterization problems: biometrics estimation (including body fat, muscle,\nwater, and bone rates) and person recognition. We also demonstrated the\napplication of CSI-Net on two distinctive pose recognition tasks: the hand sign\nrecognition (fine-scaled action of the hand) and falling detection\n(coarse-scaled motion of the body).","url_abs":"http://arxiv.org/abs/1810.03064v2","url_pdf":"http://arxiv.org/pdf/1810.03064v2.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":"csi-net-unified-human-body-characterization","repo_url":"https://github.com/geekfeiw/CSI-Net","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"person-recognition","task_name":"Person Recognition"},{"task_slug":"action-recognition","task_name":"Temporal Action Localization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}