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Learning visual representations for compositional analysis of artworks and photographs
Fatemeh Behrad, Tinne Tuytelaars, Johan Wagemans
Composition, the deliberate arrangement of visual elements, is central to how meaning, emotion, and aesthetic quality are conveyed in artwork, yet it remains among the least formal…
DODA: A Database of Datasets for Aesthetics Research
Lisa Koßmann, Ralf Bartho, Christoph Redies +1
With rapid growth in the fields of empirical and computational aesthetics we have seen a vast increase in large image datasets annotated for aesthetics. As the image databases diff…
Personalizing Text-to-Image Generation to Individual Taste
Anne-Sofie Maerten, Juliane Verwiebe, Shyamgopal Karthik +3
Modern text-to-image (T2I) models generate high-fidelity visuals but remain indifferent to individual user preferences. While existing reward models optimize for "average" human ap…
From Concepts to Judgments: Interpretable Image Aesthetic Assessment
Xiao-Chang Liu, Johan Wagemans
Image aesthetic assessment (IAA) aims to predict the aesthetic quality of images as perceived by humans. While recent IAA models achieve strong predictive performance, they offer l…
Charm: The Missing Piece in ViT fine-tuning for Image Aesthetic Assessment
Fatemeh Behrad, Tinne Tuytelaars, Johan Wagemans
The capacity of Vision transformers (ViTs) to handle variable-sized inputs is often constrained by computational complexity and batch processing limitations. Consequently, ViTs are…
LAPIS: A novel dataset for personalized image aesthetic assessment
Anne-Sofie Maerten, Li-Wei Chen, Stefanie De Winter +2
We present the Leuven Art Personalized Image Set (LAPIS), a novel dataset for personalized image aesthetic assessment (PIAA). It is the first dataset with images of artworks that i…