Self-Adaptive Computational Aesthetic Evaluation of Chinese Ink Paintings Based on Deep Learning

Abstract

: Computational aesthetic evaluation of artworks has become an active research direction in recent years. However, current works mainly focus on oil paintings and photographs, there have been few attempts in quantitative aesthetic evaluation of Chinese ink paintings. Chinese ink painting uses ink blended with water and a variation of brushwork to depict picture, which differs significantly from photographs and oil paintings in visual features, semantic features, and aesthetic principles. Aiming at this problem, we propose a framework of self-adaptive computational aesthetic evaluation of Chinese ink paintings based on deep learning technique. Firstly, we build an aesthetic evaluation standard dataset for ink painting images. Sec-ondly, according to aesthetic principles of Chinese ink paintings, we design a multi-view parallel deep neural