Abstract:Convolutional neural networks (CNNs) are commonly employed for image emotion recognition owing to their ability to extract local features; however, they have difficulty capturing the global representations of images. In contrast, self-attention modules in a visual transformer network can capture long-range dependencies as global features. Some studies have shown that an image's local and global features determine the emotions of the image and that some local regions can generate an emotional prioritization eff… Show more
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