AVAtt : Art Visual Attention dataset for diverse painting styles
Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani, Alessandro Bruno · 2024
Preserving cultural heritage is paramount for societal and historical identity. Paintings, spanning ancient to modern eras, are pivotal subjects under constant scrutiny. As art reflects human creativity, studying human visual behavior toward paintings becomes increasingly vital. Thus, we introduce the AVAtt dataset, providing eye movement data for a diverse collection of painting styles across various ages and geographical origins. This dataset aims to facilitate the development and evaluation of computational saliency and scanpath prediction methods in the unique domain of painting (Dataset available at Github).