{"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/okutama-action-an-aerial-view-video-dataset","title":"Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection","arxiv_id":"1706.03038","date":"2017-06-09","proceeding":null,"authors":["Mohammadamin Barekatain","Miquel Martí","Hsueh-Fu Shih","Samuel Murray","Kotaro Nakayama","Yutaka Matsuo","Helmut Prendinger"],"abstract":"Despite significant progress in the development of human action detection\ndatasets and algorithms, no current dataset is representative of real-world\naerial view scenarios. We present Okutama-Action, a new video dataset for\naerial view concurrent human action detection. It consists of 43 minute-long\nfully-annotated sequences with 12 action classes. Okutama-Action features many\nchallenges missing in current datasets, including dynamic transition of\nactions, significant changes in scale and aspect ratio, abrupt camera movement,\nas well as multi-labeled actors. As a result, our dataset is more challenging\nthan existing ones, and will help push the field forward to enable real-world\napplications.","url_abs":"http://arxiv.org/abs/1706.03038v2","url_pdf":"http://arxiv.org/pdf/1706.03038v2.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-detection","task_name":"Action Detection"}],"methods":[],"datasets_introduced":[{"slug":"okutama-action","name":"Okutama-Action","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1706.03038","atlas_url":"https://app.syntology.ai/?focus=1706.03038","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}