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cs.CV2026

Deep Sprite-based Image Models: An Analysis

Zeynep Sonat Baltacı, Romain Loiseau, Mathieu Aubry

While foundation models drive steady progress in image segmentation and diffusion algorithms compose always more realistic images, the seemingly simple problem of identifying recur…

cs.CV2026

Text region detection in historical astronomical diagrams

Zeynep Sonat Baltacı, Raphaël Baena, Fei Meng +4

Text detection is a crucial task in the analysis of historical documents. While datasets and benchmarks exist for text detection in manuscripts and maps, the study of text in mathe…

cs.CV2026

Leveraging Morphology for Historical Script Metrological Analysis

Malamatenia Vlachou Efstathiou, Raphaël Baena, Dominique Stutzmann +1

Advances in handwritten text recognition have enabled large-scale transcription of historical documents, but still provide limited access to interpretable visual measurements for p…

cs.CV2024

An Interpretable Deep Learning Approach for Morphological Script Type Analysis

Malamatenia Vlachou-Efstathiou, Ioannis Siglidis, Dominique Stutzmann +1

Defining script types and establishing classification criteria for medieval handwriting is a central aspect of palaeographical analysis. However, existing typologies often encounte…

cs.CV2024

Diffusion Models as Data Mining Tools

Ioannis Siglidis, Aleksander Holynski, Alexei A. Efros +2

This paper demonstrates how to use generative models trained for image synthesis as tools for visual data mining. Our insight is that since contemporary generative models learn an…