{"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/subspace-clustering-for-action-recognition","title":"Subspace Clustering for Action Recognition with Covariance Representations and Temporal Pruning","arxiv_id":"2006.11812","date":"2020-06-21","proceeding":null,"authors":["Giancarlo Paoletti","Jacopo Cavazza","Cigdem Beyan","Alessio Del Bue"],"abstract":"This paper tackles the problem of human action recognition, defined as classifying which action is displayed in a trimmed sequence, from skeletal data. Albeit state-of-the-art approaches designed for this application are all supervised, in this paper we pursue a more challenging direction: Solving the problem with unsupervised learning. To this end, we propose a novel subspace clustering method, which exploits covariance matrix to enhance the action's discriminability and a timestamp pruning approach that allow us to better handle the temporal dimension of the data. Through a broad experimental validation, we show that our computational pipeline surpasses existing unsupervised approaches but also can result in favorable performances as compared to supervised methods.","url_abs":"https://arxiv.org/abs/2006.11812v1","url_pdf":"https://arxiv.org/pdf/2006.11812v1.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":"subspace-clustering-for-action-recognition","repo_url":"https://github.com/IIT-PAVIS/subspace-clustering-action-recognition","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"skeleton-based-action-recognition","task_name":"Skeleton Based Action Recognition"}],"methods":[{"method_slug":"pruning","method_name":"Pruning"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/skeleton-based-action-recognition-on-florence","task":"Skeleton Based Action Recognition","dataset":"Florence 3D","model":"Temporal Spectral Clustering + Temporal Subspace Clustering","rank_in_archive_order":4,"of":7,"metrics":{"Accuracy":"95.81%"},"uses_additional_data":false},{"leaderboard":"/sota/skeleton-based-action-recognition-on-gaming","task":"Skeleton Based Action Recognition","dataset":"Gaming 3D (G3D)","model":"Temporal K-Means Clustering + Temporal Covariance Subspace Clustering","rank_in_archive_order":2,"of":4,"metrics":{"Accuracy":"92.91%"},"uses_additional_data":false},{"leaderboard":"/sota/skeleton-based-action-recognition-on-hdm05","task":"Skeleton Based Action Recognition","dataset":"HDM05","model":"Temporal Subspace Clustering","rank_in_archive_order":1,"of":1,"metrics":{"Accuracy":"89.80%"},"uses_additional_data":false},{"leaderboard":"/sota/skeleton-based-action-recognition-on-msr","task":"Skeleton Based Action Recognition","dataset":"MSR Action3D","model":"Temporal K-Means Clustering + Temporal Subspace Clustering","rank_in_archive_order":2,"of":4,"metrics":{"Accuracy":"88.51%"},"uses_additional_data":false},{"leaderboard":"/sota/skeleton-based-action-recognition-on-msr-1","task":"Skeleton Based Action Recognition","dataset":"MSR ActionPairs","model":"Temporal Subspace Clustering","rank_in_archive_order":1,"of":1,"metrics":{"Accuracy":"98.02%"},"uses_additional_data":false},{"leaderboard":"/sota/skeleton-based-action-recognition-on-msrc-12","task":"Skeleton Based Action Recognition","dataset":"MSRC-12","model":"Temporal Subspace Clustering","rank_in_archive_order":1,"of":2,"metrics":{"Accuracy":"99.08%"},"uses_additional_data":false},{"leaderboard":"/sota/skeleton-based-action-recognition-on-ut","task":"Skeleton Based Action Recognition","dataset":"UT-Kinect","model":"Temporal Subspace Clustering","rank_in_archive_order":1,"of":7,"metrics":{"Accuracy":"99.50%"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2006.11812","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}