Self-Relevance Predicts the Aesthetic Appeal of Real and Synthetic Artworks Generated via Neural Style Transfer
Vessel EA, Borges Bastos Pasqualette LB, Uran C, Koldehoff S, Bignardi G, Vinck M (2023)
Publication Type: Journal article
Publication year: 2023
Journal
DOI: 10.1177/09567976231188107
Abstract
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.
Authors with CRIS profile
Involved external institutions
Max-Planck-Institut für Empirische Ästhetik / Max Planck Institute for Empirical Aesthetics (MPIEA)
Germany (DE)
Ernst Strüngmann Institut (ESI) / Ernst Strüngmann Institute for Neuroscience
Germany (DE)
Max Planck Institute for Psycholinguistics / Max-Planck-Institut für Psycholinguistik
Netherlands (NL)
Germany (DE)
Ernst Strüngmann Institut (ESI) / Ernst Strüngmann Institute for Neuroscience
Germany (DE)
Max Planck Institute for Psycholinguistics / Max-Planck-Institut für Psycholinguistik
Netherlands (NL)
How to cite
APA:
Vessel, E.A., Borges Bastos Pasqualette, L.B., 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. https://dx.doi.org/10.1177/09567976231188107
MLA:
Vessel, Edward A., et al. "Self-Relevance Predicts the Aesthetic Appeal of Real and Synthetic Artworks Generated via Neural Style Transfer." Psychological Science (2023).
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