Image Aesthetics Assessment Based on Hypernetwork of Emotion Fusion

作者：Guipeng Lan, Shuai Xiao, Jiachen Yang, Yanshuang Zhou, Jiabao Wen, Wen Lu, Xinbo Gao · 发表于：IEEE Transactions on Multimedia · 年份：2023 · DOI：10.1109/tmm.2023.3313507 · 被引用次数：22 · 研究领域：Visual Attention and Saliency Detection、Advanced Image Fusion Techniques、Aesthetic Perception and Analysis

Research in psychology demonstrates that visual features and semantic content can convey various emotions. Furthermore, studies have proved that image emotion and aesthetics are inextricably linked. During the image aesthetic assessment process (IAA), images elicit emotional responses from individuals, leading to emotional resonance and influencing the evaluation of images. This article proposes an image aesthetics assessment method based on hypernetwork of emotion fusion (HNEF). Our method incorporates the emotions depicted in images into the process of IAA. To accomplish this, we extract both aesthetic and emotional features from the images. Additionally, we employed the self-attention mechanism of the transformer to comprehensively investigate the intimate connection between aesthetics and emotion. Additionally, the hypernetwork is designed to establish perception rules governing the high-level semantic information in images. The experimental results validate the strong correlation between emotion and aesthetics. Furthermore, the proposed method exhibits a significantly competitive advantage when compared to existing methods on the Aesthetic Visual Analysis (AVA) dataset.