This paper describes the MediaEval 2020 \textit{Predicting Media Memorability} task. After first being proposed at MediaEval 2018, the Predicting Media Memorability task is in its 3rd edition this year, as the prediction of short-term and long-term video memorability (VM) remains a challenging task. In 2020, the format remained the same as in previous editions. This year the videos are a subset of the TRECVid 2019 Video-to-Text dataset, containing more action rich video content as compared with the 2019 task. In this paper a description of some aspects of this task is provided, including its main characteristics, a description of the collection, the ground truth dataset, evaluation metrics and the requirements for participants' run submissions.

中文翻译：

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MediaEval 2020概述预测媒体的可记忆性任务：什么使视频令人难忘？

本文介绍了MediaEval 2020 \ textit {Predicting Media Memorability}任务。在MediaEval 2018上首次提出之后，预测媒体可存储性任务将在今年的第三版中发布，因为预测短期和长期视频可存储性（VM）仍然是一项艰巨的任务。2020年，格式与以前的版本相同。今年的视频是TRECVid 2019视频到文本数据集的子集，与2019任务相比，包含更多的动作丰富视频内容。在本文中，提供了该任务某些方面的描述，包括其主要特征，集合的描述，地面真相数据集，评估指标以及参与者跑步提交的要求。