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New dataset XPASS-Vis enables cross-domain personalized image aesthetic assessment

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Researchers have introduced XPASS-Vis, a novel dataset designed to explore personalized image aesthetic assessment across different visual domains. The dataset includes over 6,500 images from art, fashion, and landscape categories, rated by 129 annotators. Initial experiments using unsupervised domain adaptation show that personalized aesthetic preferences can be transferred across domains with moderate success, though a significant gap remains for PIAA-specific adaptation strategies. AI

RANK_REASON The cluster describes a new academic dataset and associated research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset XPASS-Vis enables cross-domain personalized image aesthetic assessment

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The cluster describes a new academic dataset and associated research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.4]
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  1. arXiv cs.CV TIER_1 English(EN) · Takato Hayashi, Hiroaki Takahara, Candy Olivia Mawalim, Hiromi Narimatsu, Akisato Kimura, Shiro Kumano, Shogo Okada ·

    XPASS-Vis: A Dataset for Cross-Domain Personalized Image Aesthetic Assessment

    arXiv:2606.15629v1 Announce Type: new Abstract: Personalized image aesthetic assessment (PIAA) seeks to model, at the individual level, the subjective nature of aesthetic judgments toward artworks and photographs. Aesthetic preference is known to be both deeply personal and parti…

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