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Multimodal Sentiment Analysis

Multimodal sentiment analysis is the task of performing sentiment analysis with multiple data sources - e.g. a camera feed of someone's face and their recorded speech.

( Image credit: ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection )

Papers

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Showing 11–20 of 202 papers

TitleStatusHype
MSE-Adapter: A Lightweight Plugin Endowing LLMs with the Capability to Perform Multimodal Sentiment Analysis and Emotion RecognitionCode1
LLaVAC: Fine-tuning LLaVA as a Multimodal Sentiment ClassifierCode0
Multi-Modality Collaborative Learning for Sentiment AnalysisCode1
Dynamic Multimodal Sentiment Analysis: Leveraging Cross-Modal Attention for Enabled Classification—0
Modality-Invariant Bidirectional Temporal Representation Distillation Network for Missing Multimodal Sentiment Analysis—0
Seek Common Ground While Reserving Differences: Semi-Supervised Image-Text Sentiment Recognition—0
DLF: Disentangled-Language-Focused Multimodal Sentiment AnalysisCode2
Semi-IIN: Semi-supervised Intra-inter modal Interaction Learning Network for Multimodal Sentiment AnalysisCode1
Enriching Multimodal Sentiment Analysis through Textual Emotional Descriptions of Visual-Audio Content—0
Multimodal Sentiment Analysis based on Video and Audio Inputs—0
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