{"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/when-will-you-do-what-anticipating-temporal","title":"When will you do what? - Anticipating Temporal Occurrences of Activities","arxiv_id":"1804.00892","date":"2018-04-03","proceeding":"CVPR 2018 6","authors":["Yazan Abu Farha","Alexander Richard","Juergen Gall"],"abstract":"Analyzing human actions in videos has gained increased attention recently.\nWhile most works focus on classifying and labeling observed video frames or\nanticipating the very recent future, making long-term predictions over more\nthan just a few seconds is a task with many practical applications that has not\nyet been addressed. In this paper, we propose two methods to predict a\nconsiderably large amount of future actions and their durations. Both, a CNN\nand an RNN are trained to learn future video labels based on previously seen\ncontent. We show that our methods generate accurate predictions of the future\neven for long videos with a huge amount of different actions and can even deal\nwith noisy or erroneous input information.","url_abs":"http://arxiv.org/abs/1804.00892v1","url_pdf":"http://arxiv.org/pdf/1804.00892v1.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":"when-will-you-do-what-anticipating-temporal","repo_url":"https://github.com/yabufarha/anticipating-activities","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1804.00892","atlas_url":"https://app.syntology.ai/?focus=1804.00892","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}