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arxiv 2504.07670 v1 pith:V4JWLBTM submitted 2025-04-10 cs.CV

LAPIS: A novel dataset for personalized image aesthetic assessment

classification cs.CV
keywords imagelapisattributesaestheticassessmentdatasetpersonalpersonalized
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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 is suitable for PIAA. LAPIS consists of 11,723 images and was meticulously curated in collaboration with art historians. Each image has an aesthetics score and a set of image attributes known to relate to aesthetic appreciation. Besides rich image attributes, LAPIS offers rich personal attributes of each annotator. We implemented two existing state-of-the-art PIAA models and assessed their performance on LAPIS. We assess the contribution of personal attributes and image attributes through ablation studies and find that performance deteriorates when certain personal and image attributes are removed. An analysis of failure cases reveals that both existing models make similar incorrect predictions, highlighting the need for improvements in artistic image aesthetic assessment. The LAPIS project page can be found at: https://github.com/Anne-SofieMaerten/LAPIS

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