Towards Hierarchical Structure Understanding of Newspaper Images
Understanding newspaper images remains a challenging task due to their complex, nested hierarchical structures and dense, heterogeneous layouts. In this paper, we explore two complementary approaches for newspaper structure understanding. First, we present a modular bottom-up pipeline that combines state-of-the-art open-source models: YOLO for layout detection, LayoutReader for reading order prediction, and a custom algorithm for article segmentation. This approach leverages existing robust components while maintaining flexibility and interpretability. Second, we introduce Tiramisu (Tiered Tra
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- PossiblePossibly related (embedding) · 48%Structured PDF-to-JSON: A Guide to Open-Source Extraction Models in 2026 - MarkTechPost →
- FuzzyOverlapping authors or contributors · 62%AstrBotDevs/AstrBot →
“Shared author/contributor keys: simon”
- LinkedLinked via arxiv author · 85%William Mocaër →
“Towards Hierarchical Structure Understanding of Newspaper Images”
- LinkedLinked via arxiv author · 85%Solène Tarride →
“Towards Hierarchical Structure Understanding of Newspaper Images”
- LinkedLinked via arxiv author · 85%Thomas Constum →
“Towards Hierarchical Structure Understanding of Newspaper Images”
- LinkedLinked via arxiv author · 85%Merveilles Agbeti-Messan →
“Towards Hierarchical Structure Understanding of Newspaper Images”
- LinkedLinked via arxiv author · 85%Tom Simon →
“Towards Hierarchical Structure Understanding of Newspaper Images”
- LinkedLinked via arxiv author · 85%Clément Chatelain →
“Towards Hierarchical Structure Understanding of Newspaper Images”