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  Self-relevance predicts the aesthetic appeal of real and synthetic artworks generated via neural style transfer

Vessel, E. A., Pasqualette, L., Uran, C., Koldehoff, S., Bignardi, G., & Vinck, M. (2023). Self-relevance predicts the aesthetic appeal of real and synthetic artworks generated via neural style transfer. Psychological Science, 34(9), 1007-1023. doi:10.1177/09567976231188107.

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© The Author(s) 2023. Creative Commons License (CC BY 4.0) This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages

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 Urheber:
Vessel, Edward A.1, Autor
Pasqualette, Laura2, Autor
Uran, Cem3, 4, Autor
Koldehoff, Sarah1, Autor
Bignardi, Giacomo5, 6, Autor           
Vinck, Martin3, 4, Autor
Affiliations:
1Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany, ou_persistent22              
2Friedrich-Alexander University Erlangen-Nürnberg, Erlangen-Nürnberg, Germany, ou_persistent22              
3Ernst Strüngmann Institute, Frankfurt am Main, Germany, ou_persistent22              
4Donders Centre for Neuroscience, Nijmegen, The Netherlands, ou_persistent22              
5Language and Genetics Department, MPI for Psycholinguistics, Max Planck Society, ou_792549              
6Max Planck School of Cognition, ou_persistent22              

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 Zusammenfassung: What determines the aesthetic appeal of artworks? Recent work suggests that aesthetic appeal can, to some extent, be predicted from a visual artwork’s image features. Yet a large fraction of variance in aesthetic ratings remains unexplained and may relate to individual preferences. We hypothesized that an artwork’s aesthetic appeal depends strongly on self-relevance. In a first study (N = 33 adults, online replication N = 208), rated aesthetic appeal for real artworks was positively predicted by rated self-relevance. In a second experiment (N = 45 online), we created synthetic, self-relevant artworks using deep neural networks that transferred the style of existing artworks to photographs. Style transfer was applied to self-relevant photographs selected to reflect participant-specific attributes such as autobiographical memories. Self-relevant, synthetic artworks were rated as more aesthetically appealing than matched control images, at a level similar to human-made artworks. Thus, self-relevance is a key determinant of aesthetic appeal, independent of artistic skill and image features.

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Sprache(n): eng - English
 Datum: 2023-08-142023
 Publikationsstatus: Erschienen
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 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1177/09567976231188107
 Art des Abschluß: -

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Titel: Psychological Science
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Malden, MA : Blackwell Publishers
Seiten: - Band / Heft: 34 (9) Artikelnummer: - Start- / Endseite: 1007 - 1023 Identifikator: ISSN: 0956-7976
CoNE: https://pure.mpg.de/cone/journals/resource/974392592005