Related papers: LAPIS: A novel dataset for personalized image aesthetic assessment

LAPIS: A novel dataset for personalized image aesthetic assessment

URL: http://arxiv.org/abs/2504.07670v1
Date: Thu, 10 Apr 2025 11:42:56 GMT
Title: LAPIS: A novel dataset for personalized image aesthetic assessment
Authors: Anne-Sofie Maerten, Li-Wei Chen, Stefanie De Winter, Christophe Bossens, Johan Wagemans,
Abstract summary: Leuven Art Personalized Image Set (LAPIS) is a novel dataset for personalized image aesthetic assessment (PIAA)<n>LAPIS consists of 11,723 images and was meticulously curated in collaboration with art historians.<n>We implement two existing state-of-the-art PIAA models and assess their performance on LAPIS.
Score: 5.457078529757273
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
Abstract: 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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