{"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/a-human-annotated-video-dataset-for-training","title":"A Human-Annotated Video Dataset for Training and Evaluation of 360-Degree Video Summarization Methods","arxiv_id":"2406.02991","date":"2024-06-05","proceeding":null,"authors":["Ioannis Kontostathis","Evlampios Apostolidis","Vasileios Mezaris"],"abstract":"In this paper we introduce a new dataset for 360-degree video summarization: the transformation of 360-degree video content to concise 2D-video summaries that can be consumed via traditional devices, such as TV sets and smartphones. The dataset includes ground-truth human-generated summaries, that can be used for training and objectively evaluating 360-degree video summarization methods. Using this dataset, we train and assess two state-of-the-art summarization methods that were originally proposed for 2D-video summarization, to serve as a baseline for future comparisons with summarization methods that are specifically tailored to 360-degree video. Finally, we present an interactive tool that was developed to facilitate the data annotation process and can assist other annotation activities that rely on video fragment selection.","url_abs":"https://arxiv.org/abs/2406.02991v1","url_pdf":"https://arxiv.org/pdf/2406.02991v1.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":"a-human-annotated-video-dataset-for-training","repo_url":"https://github.com/idt-iti/360-vsumm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"video-summarization","task_name":"Video Summarization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}