{"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/pose-for-action-action-for-pose","title":"Pose for Action - Action for Pose","arxiv_id":"1603.04037","date":"2016-03-13","proceeding":null,"authors":["Umar Iqbal","Martin Garbade","Juergen Gall"],"abstract":"In this work we propose to utilize information about human actions to improve\npose estimation in monocular videos. To this end, we present a pictorial\nstructure model that exploits high-level information about activities to\nincorporate higher-order part dependencies by modeling action specific\nappearance models and pose priors. However, instead of using an additional\nexpensive action recognition framework, the action priors are efficiently\nestimated by our pose estimation framework. This is achieved by starting with a\nuniform action prior and updating the action prior during pose estimation. We\nalso show that learning the right amount of appearance sharing among action\nclasses improves the pose estimation. We demonstrate the effectiveness of the\nproposed method on two challenging datasets for pose estimation and action\nrecognition with over 80,000 test images.","url_abs":"http://arxiv.org/abs/1603.04037v2","url_pdf":"http://arxiv.org/pdf/1603.04037v2.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":[],"tasks":[{"task_slug":"action-recognition-in-videos","task_name":"Action Recognition"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"},{"task_slug":"skeleton-based-action-recognition","task_name":"Skeleton Based Action Recognition"},{"task_slug":"action-recognition","task_name":"Temporal Action Localization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/pose-estimation-on-upenn-action","task":"Pose Estimation","dataset":"UPenn Action","model":"Iqbal et al.","rank_in_archive_order":5,"of":5,"metrics":{"Mean PCK@0.2":"81.1"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1603.04037","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}