Recognizing human feelings from image and text is a core challenge of multi-modal data analysis, often applied in personalized advertising. Previous works aim at exploring the shared features, which are the matched contents between images and texts. However, the modality-dependent sentiment information (private features) in each modality is usually ignored by cross-modal interactions, the real sentiment is often reflected in one modality. In this paper, we propose a Modality-Dependent Sentiment Exploring framework (MDSE). First, to exploit the private features, we compare shared features with ...
