{"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/temporal-human-action-segmentation-via","title":"Temporal Human Action Segmentation via Dynamic Clustering","arxiv_id":"1803.05790","date":"2018-03-15","proceeding":null,"authors":["Yan Zhang","He Sun","Siyu Tang","Heiko Neumann"],"abstract":"We present an effective dynamic clustering algorithm for the task of temporal\nhuman action segmentation, which has comprehensive applications such as\nrobotics, motion analysis, and patient monitoring. Our proposed algorithm is\nunsupervised, fast, generic to process various types of features, and\napplicable in both the online and offline settings. We perform extensive\nexperiments of processing data streams, and show that our algorithm achieves\nthe state-of-the-art results for both online and offline settings.","url_abs":"http://arxiv.org/abs/1803.05790v2","url_pdf":"http://arxiv.org/pdf/1803.05790v2.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":"temporal-human-action-segmentation-via","repo_url":"https://github.com/yz-cnsdqz/dynamic_clustering","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"action-segmentation","task_name":"Action Segmentation"},{"task_slug":"clustering","task_name":"Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}