{"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-modeling-approaches-for-large-scale","title":"Temporal Modeling Approaches for Large-scale Youtube-8M Video Understanding","arxiv_id":"1707.04555","date":"2017-07-14","proceeding":null,"authors":["Fu Li","Chuang Gan","Xiao Liu","Yunlong Bian","Xiang Long","Yandong Li","Zhichao Li","Jie zhou","Shilei Wen"],"abstract":"This paper describes our solution for the video recognition task of the\nGoogle Cloud and YouTube-8M Video Understanding Challenge that ranked the 3rd\nplace. Because the challenge provides pre-extracted visual and audio features\ninstead of the raw videos, we mainly investigate various temporal modeling\napproaches to aggregate the frame-level features for multi-label video\nrecognition. Our system contains three major components: two-stream sequence\nmodel, fast-forward sequence model and temporal residual neural networks.\nExperiment results on the challenging Youtube-8M dataset demonstrate that our\nproposed temporal modeling approaches can significantly improve existing\ntemporal modeling approaches in the large-scale video recognition tasks. To be\nnoted, our fast-forward LSTM with a depth of 7 layers achieves 82.75% in term\nof GAP@20 on the Kaggle Public test set.","url_abs":"http://arxiv.org/abs/1707.04555v1","url_pdf":"http://arxiv.org/pdf/1707.04555v1.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-modeling-approaches-for-large-scale","repo_url":"https://github.com/baidu/Youtube-8M","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"paddle","reach":null}],"tasks":[{"task_slug":"video-recognition","task_name":"Video Recognition"},{"task_slug":"video-understanding","task_name":"Video Understanding"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1707.04555","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}