Papers by Zhangmeizhi Li

1 papers
Tackling Modality Heterogeneity with Multi-View Calibration Network for Multimodal Sentiment Detection (2023.acl-long)

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Challenge: Existing studies focus on fusing different features but ignore the challenge of modality heterogeneity.
Approach: They propose a text-guided fusion module with novel Sparse-Attention to reduce the negative impacts of redundant visual elements and a sentiment-based congruity constraint task to calibrate the feature shift in the representation space.
Outcome: The proposed model is competitive against existing methods and achieves state-of-the-art results on two public benchmark datasets.

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