The Southern Song aesthetics of simplicity, detachment, and reverence for nature exerted a profound influence on East Asian ink painting. Yet existing scholarship has limited adoption of systematic quantitative approaches. This study applies a machine learning—based image block entropy model to quantitatively examine compositional patterns in figure paintings by Liang Kai, Muqi, and Sesshū Tōyō. The analysis reveals shared technical and iconographic tendencies, including consistently lower-central placement of the primary subject, prominent upper inscriptions, and deliberately sparse backgrounds—features that together establish a “lowered center of gravity” composition distinct from the conventions of court painting. Sesshū adapted these traditions, utilizing bold lines and intricate detail, which resonated with Japanese aesthetic sensibilities. Compared to academic rigidity, Sesshū’s compositions emphasize spontaneity, reflecting Zen improvisation. By integrating computational modeling with art-historical inquiry, this study advances a replicable quantitative framework for analyzing the cross-cultural transmission and transformation of Zen painting styles.
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Rongrong Fu
East China University of Science and Technology
Junxuan Li
East China University of Science and Technology
Ruiyang Fan
East China University of Science and Technology
East China University of Science and Technology
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Fu et al. (Thu,) studied this question.
synapsesocial.com/papers/69a286b80a974eb0d3c01e36 — DOI: https://doi.org/10.1038/s40494-026-02297-x
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