In this paper, we present a novel problem, namely video timeline modeling.
Our objective is to create a video-associated timeline from a set of videos
related to a specific topic, thereby facilitating the content and structure
understanding of the story being told. This problem has significant potential
in various real-world applications, such as news story summarization. To
bootstrap research in this area, we curate a realistic benchmark dataset,
YouTube-News-Timeline, consisting of over $12$k timelines and $300$k YouTube
news videos. Additionally, we propose a set of quantitative metrics as the
protocol to comprehensively evaluate and compare methodologies. With such a
testbed, we further develop and benchmark exploratory deep learning approaches
to tackle this problem. We anticipate that this exploratory work will pave the
way for further research in video timeline modeling. The assets are available
via
this https URL

本研究提出了一个新颖的问题，即视频时间轴建模，目的是通过一组与特定主题相关的视频创建与视频相关的时间轴，从而促进对所讲述故事的内容和结构的理解。通过构建一个现实的基准数据集 YouTube-News-Timeline，并提出了一套量化指标来全面评估和比较方法，我们进一步开发和评估了探索性的深度学习方法来解决这个问题。我们预计这项开拓性工作将为视频时间轴建模的进一步研究铺平道路。