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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 81–90 of 202 papers

TitleStatusHype
Exploring Multimodal Sentiment Analysis via CBAM Attention and Double-layer BiLSTM Architecture—0
MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation ModelsCode1
Curriculum Learning Meets Weakly Supervised Modality Correlation Learning—0
UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion RecognitionCode2
A Self-Adjusting Fusion Representation Learning Model for Unaligned Text-Audio Sequences—0
Few-shot Multimodal Sentiment Analysis based on Multimodal Probabilistic Fusion PromptsCode1
MARLIN: Masked Autoencoder for facial video Representation LearnINgCode2
Multimodal Information Bottleneck: Learning Minimal Sufficient Unimodal and Multimodal RepresentationsCode1
Improving the Modality Representation with Multi-View Contrastive Learning for Multimodal Sentiment Analysis—0
On the Use of Modality-Specific Large-Scale Pre-Trained Encoders for Multimodal Sentiment AnalysisCode0
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