构建首个漫画场景级叙事数据集，推动多模态故事理解研究。
ComicScene154: A Scene Dataset for Comic Analysis
- 从154部公开漫画中人工标注场景级叙事弧线
- 提出基线分割流程，为后续研究提供基准
- 助力NLP领域拓展漫画分析与跨模态叙事研究
漫画作为一种融合文本与图像的独特叙事媒介，其计算叙事分析仍处于起步阶段。我们提出了ComicScene154，一个涵盖多元题材的公共领域漫画书场景级叙事弧线手动标注数据集。通过将漫画视为以叙事驱动的多模态数据抽象，凸显其对更广泛多模态叙事研究的价值。为验证数据集效用，我们构建了一个基线场景分割流程，为未来研究提供初步基准。实验表明，ComicScene154是推进多模态叙事理解计算方法的重要资源，并有望拓展自然语言处理领域的漫画分析边界。
原文摘要 · Abstract (English)
Comics offer a compelling yet under-explored domain for computational narrative analysis, combining text and imagery in ways distinct from purely textual or audiovisual media. We introduce ComicScene154, a manually annotated dataset of scene-level narrative arcs derived from public-domain comic books spanning diverse genres. By conceptualizing comics as an abstraction for narrative-driven, multimodal data, we highlight their potential to inform broader research on multi-modal storytelling. To demonstrate the utility of ComicScene154, we present a baseline scene segmentation pipeline, providing an initial benchmark that future studies can build upon. Our results indicate that ComicScene154 constitutes a valuable resource for advancing computational methods in multimodal narrative understanding and expanding the scope of comic analysis within the Natural Language Processing community.
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