{"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/phd-gifs-personalized-highlight-detection-for","title":"PHD-GIFs: Personalized Highlight Detection for Automatic GIF Creation","arxiv_id":"1804.06604","date":"2018-04-18","proceeding":null,"authors":["Ana García del Molino","Michael Gygli"],"abstract":"Highlight detection models are typically trained to identify cues that make\nvisual content appealing or interesting for the general public, with the\nobjective of reducing a video to such moments. However, the \"interestingness\"\nof a video segment or image is subjective. Thus, such highlight models provide\nresults of limited relevance for the individual user. On the other hand,\ntraining one model per user is inefficient and requires large amounts of\npersonal information which is typically not available. To overcome these\nlimitations, we present a global ranking model which conditions on each\nparticular user's interests. Rather than training one model per user, our model\nis personalized via its inputs, which allows it to effectively adapt its\npredictions, given only a few user-specific examples. To train this model, we\ncreate a large-scale dataset of users and the GIFs they created, giving us an\naccurate indication of their interests. Our experiments show that using the\nuser history substantially improves the prediction accuracy. On our test set of\n850 videos, our model improves the recall by 8% with respect to generic\nhighlight detectors. Furthermore, our method proves more precise than the\nuser-agnostic baselines even with just one person-specific example.","url_abs":"http://arxiv.org/abs/1804.06604v2","url_pdf":"http://arxiv.org/pdf/1804.06604v2.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":"phd-gifs-personalized-highlight-detection-for","repo_url":"https://github.com/gyglim/personalized-highlights-dataset","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"highlight-detection","task_name":"Highlight Detection"}],"methods":[],"datasets_introduced":[{"slug":"phd2","name":"PHD²","full_name":"Personalized Highlight Detection Dataset"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1804.06604","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}