The persistence of painting styles

Fuente: arXiv
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Main Authors: Munnangi, Reetikaa Reddy, Giunti, Barbara
Format: Preprint
Published: 2025
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author Munnangi, Reetikaa Reddy
Giunti, Barbara
author_facet Munnangi, Reetikaa Reddy
Giunti, Barbara
contents Art is a deeply personal and expressive medium, where each artist brings their own style, technique, and cultural background into their work. Traditionally, identifying artistic styles has been the job of art historians or critics, relying on visual intuition and experience. However, with the advancement of mathematical tools, we can explore art through more structured lens. In this work, we show how persistent homology (PH), a method from topological data analysis, provides objective and interpretable insights on artistic styles. We show how PH can, with statistical certainty, differentiate between artists, both from different artistic currents and from the same one, and distinguish images of an artist from an AI-generated image in the artist's style.
format Preprint
id arxiv_https___arxiv_org_abs_2511_16695
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The persistence of painting styles
Munnangi, Reetikaa Reddy
Giunti, Barbara
Computer Vision and Pattern Recognition
Art is a deeply personal and expressive medium, where each artist brings their own style, technique, and cultural background into their work. Traditionally, identifying artistic styles has been the job of art historians or critics, relying on visual intuition and experience. However, with the advancement of mathematical tools, we can explore art through more structured lens. In this work, we show how persistent homology (PH), a method from topological data analysis, provides objective and interpretable insights on artistic styles. We show how PH can, with statistical certainty, differentiate between artists, both from different artistic currents and from the same one, and distinguish images of an artist from an AI-generated image in the artist's style.
title The persistence of painting styles
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2511.16695