Galleries, libraries, archives, and museums are nowadays striving to implement innovative
approaches to adequately use and distribute the wealth of knowledge found in cultural …

CLIP is a powerful and widely used tool for understanding images in the context of natural
language descriptions to perform nuanced tasks. However, it does not offer application …

Cultural heritage applications and advanced machine learning models are creating a fruitful
synergy to provide effective and accessible ways of interacting with artworks. Smart audio …

Abstract This paper introduces Art_GenEvalGPT, a novel dataset of synthetic dialogues
centered on art generated through ChatGPT. Unlike existing datasets focused on …

Museums serve as vital repositories of cultural heritage and historical artifacts spanning
diverse epochs, civilizations, and regions, preserving well-documented collections. Data …

Visual question answering (VQA) is a challenging task that requires models to understand
both visual and linguistic inputs and produce accurate answers. However, VQA models often …

Recent advancements in unsupervised object re-identification have witnessed remarkable
progress, which usually focuses on capturing fine-grained semantic information through …

Large vision-language models (VLMs) have demonstrated remarkable abilities in
understanding everyday content. However, their performance in the domain of art …

While AI techniques have enabled automated analysis and interpretation of visual content,
generating meaningful captions for artworks presents unique challenges. These include …

To enhance the museum experience for visitors, it's crucial to adopt a people-centered
approach. This means engaging with visitors dynamically, providing transformative learning …