SoccerHigh: a benchmark dataset for automatic soccer video summarization

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  • dc.contributor.author Díaz-Juan, Artur
  • dc.contributor.author Ballester, Coloma
  • dc.contributor.author Haro Ortega, Gloria
  • dc.date.accessioned 2025-10-30T07:51:15Z
  • dc.date.available 2025-10-30T07:51:15Z
  • dc.date.issued 2025
  • dc.description.abstract Video summarization aims to extract key shots from longer videos to produce concise and informative summaries. One of its most common applications is in sports, where highlight reels capture the most important moments of a game, along with notable reactions and specific contextual events. Automatic summary generation can support video editors in the sports media industry by reducing the time and effort required to identify key segments. However, the lack of publicly available datasets poses a challenge in developing robust models for sports highlight generation. In this paper, we address this gap by introducing a curated dataset for soccer video summarization, designed to serve as a benchmark for the task. The dataset includes shot boundaries for 237 matches from the Spanish, French, and Italian leagues, using broadcast footage sourced from the SoccerNet dataset. Alongside the dataset, we propose a baseline model specifically designed for this task, which achieves an F1 score of 0.3956 in the test set. Furthermore, we propose a new metric constrained by the length of each target summary, enabling a more objective evaluation of the generated content. The dataset and code are available at https://ipcv.github.io/SoccerHigh/.
  • dc.description.sponsorship This work was funded by the European Union (GA 101119800 - EMERALD). The authors also acknowledge the EuroHPC Joint Undertaking for awarding us access to Karolina at IT4Innovations, Czech Republic and to MareNostrum5 at the Barcelona Supercomputing Center (BSC), Spain. A. D.-J. would like to sincerely thank Dr. Alejandro Cartas for his invaluable support throughout this research.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Díaz-Juan A, Ballester C, Haro G. SoccerHigh: a benchmark dataset for automatic soccer video summarization. In: Proceedings of the 8th International ACM Workshop on Multimedia Content Analysis in Sports (MMSports '25); 2025 Oct 27-31; Dublin, Ireland. New York: Association for Computing Machinery, 2025. p. 121–30. https://doi.org/10.1145/3728423.3759410
  • dc.identifier.uri http://hdl.handle.net/10230/71716
  • dc.language.iso eng
  • dc.publisher ACM Association for Computer Machinery
  • dc.relation.ispartof Proceedings of the 8th International ACM Workshop on Multimedia Content Analysis in Sports (MMSports '25); 2025 Oct 27-31; Dublin, Ireland. New York: Association for Computing Machinery, 2025.
  • dc.rights This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. © 2025 Copyright held by the owner/author(s).
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0
  • dc.subject.keyword Sports video understanding
  • dc.subject.keyword Soccer highlights
  • dc.subject.keyword Video summarization
  • dc.subject.keyword Computer vision
  • dc.subject.keyword Deep learning
  • dc.title SoccerHigh: a benchmark dataset for automatic soccer video summarization
  • dc.type info:eu-repo/semantics/conferenceObject
  • dc.type.version info:eu-repo/semantics/acceptedVersion

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