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English(EN) SoccerNet-FoulRet: Retrieving Semantically Similar Soccer Foul Videos

新基准通过语义视频检索解决足球犯规不一致问题

研究人员推出 SoccerNet-FoulRet,这是一个新的基准,旨在通过检索语义上相似的犯规视频来解决职业足球比赛中裁判判罚不一致的问题。该系统旨在帮助裁判将有争议的犯规与相关的过往案例进行比较,而不考虑视觉差异。初步评估表明,即使是最强的零样本模型也难以完成这项任务,在人类验证的先例上 HitRate@10 低于 5%,这表明语义犯规检索仍然是一个重大挑战。 AI

影响 该基准可以通过为裁判提供与犯规判罚相关的先例来提高体育裁判的公平性。

排序理由 该集群描述了一篇介绍针对特定研究问题的新颖基准和数据集的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.IR (Information Retrieval) 阅读 →

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新基准通过语义视频检索解决足球犯规不一致问题

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该集群描述了一篇介绍针对特定研究问题的新颖基准和数据集的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Silvio Giancola ·

    SoccerNet-FoulRet: 检索语义相似的足球犯规视频

    Refereeing decisions in professional soccer remain inconsistent because referees cannot easily compare a contentious foul against similar past cases. We cast this as a retrieval problem and introduce SoccerNet-FoulRet, the first benchmark for semantic foul retrieval. Given a quer…