Dunhuang murals are gems of Chinese traditional art. This paper demonstrates a simple, yet powerful method to automatically identify the aesthetic visual style that lies in Dunhuang murals. Based on the art knowledge on Dunhuang murals, the method explicitly predicts some of possible image attributes that a human might use to understand the aesthetic visual style of a mural. These cues fall into three broad types: ① composition attributes related to mural layout or configuration; ② color attributes related to color types depicted; ③ brightness attributes related to bright conditions. We show that a classifier trained on these attributes can provide an efficient way to predict the aesthetic visual style of Dunhuang murals.
