CoSMo: A Multimodal Transformer for Page Stream Segmentation in Comic Books

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Marc Serra Ortega, Emanuele Vivoli, Artemis Llabrés, Dimosthenis Karatzas

Published: 2025, Last Modified: 14 Nov 2025CoRR 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: This paper introduces CoSMo, a novel multimodal Transformer for Page Stream Segmentation (PSS) in comic books, a critical task for automated content understanding, as it is a necessary first stage for many downstream tasks like character analysis, story indexing, or metadata enrichment. We formalize PSS for this unique medium and curate a new 20,800-page annotated dataset. CoSMo, developed in vision-only and multimodal variants, consistently outperforms traditional baselines and significantly larger general-purpose vision-language models across F1-Macro, Panoptic Quality, and stream-level metrics. Our findings highlight the dominance of visual features for comic PSS macro-structure, yet demonstrate multimodal benefits in resolving challenging ambiguities. CoSMo establishes a new state-of-the-art, paving the way for scalable comic book analysis.