{"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/uts-submission-to-google-youtube-8m-challenge","title":"UTS submission to Google YouTube-8M Challenge 2017","arxiv_id":"1707.04143","date":"2017-07-13","proceeding":null,"authors":["Linchao Zhu","Yanbin Liu","Yi Yang"],"abstract":"In this paper, we present our solution to Google YouTube-8M Video\nClassification Challenge 2017. We leveraged both video-level and frame-level\nfeatures in the submission. For video-level classification, we simply used a\n200-mixture Mixture of Experts (MoE) layer, which achieves GAP 0.802 on the\nvalidation set with a single model. For frame-level classification, we utilized\nseveral variants of recurrent neural networks, sequence aggregation with\nattention mechanism and 1D convolutional models. We achieved GAP 0.8408 on the\nprivate testing set with the ensemble model.\n  The source code of our models can be found in\n\\url{https://github.com/ffmpbgrnn/yt8m}.","url_abs":"http://arxiv.org/abs/1707.04143v1","url_pdf":"http://arxiv.org/pdf/1707.04143v1.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":"uts-submission-to-google-youtube-8m-challenge","repo_url":"https://github.com/ffmpbgrnn/yt8m","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"mixture-of-experts","task_name":"Mixture-of-Experts"},{"task_slug":"video-classification","task_name":"Video Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}