PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion Regression

• Published in: arXiv.org
• Main Authors: Zhao, Sicheng, Zizhou Jia, Chen, Hui, Li, Leida, Ding, Guiguang, Keutzer, Kurt
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 11.09.2019
• Subjects: Artificial neural networks; Computer Science - Artificial Intelligence; Computer Science - Computer Vision and Pattern Recognition; Computer Science - Multimedia; Emotions; Image classification; Polarity; Regression analysis; Source code

Existing methods on visual emotion analysis mainly focus on coarse-grained emotion classification, i.e. assigning an image with a dominant discrete emotion category. However, these methods cannot well reflect the complexity and subtlety of emotions. In this paper, we study the fine-grained regressio...