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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 51–75 of 202 papers

TitleStatusHype
Toward Robust Multimodal Learning using Multimodal Foundational Models—0
WisdoM: Improving Multimodal Sentiment Analysis by Fusing Contextual World Knowledge—0
Contextual Augmented Global Contrast for Multimodal Intent Recognition—0
MART: Masked Affective RepresenTation Learning via Masked Temporal Distribution Distillation—0
Multimodal Sentiment Analysis with Missing Modality: A Knowledge-Transfer Approach—0
Explainable Multimodal Sentiment Analysis on Bengali Memes—0
PowMix: A Versatile Regularizer for Multimodal Sentiment Analysis—0
Multimodal Sentiment Analysis: Perceived vs Induced Sentiments—0
Improving Multimodal Sentiment Analysis: Supervised Angular Margin-based Contrastive Learning for Enhanced Fusion Representation—0
Unsupervised Graph Attention Autoencoder for Attributed Networks using K-means Loss—0
Multi-label Emotion Analysis in Conversation via Multimodal Knowledge Distillation—0
Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment AnalysisCode1
Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation—0
Exchanging-based Multimodal Fusion with TransformerCode1
UniSA: Unified Generative Framework for Sentiment AnalysisCode1
Exploiting Diverse Feature for Multimodal Sentiment Analysis—0
Multimodal Multi-loss Fusion Network for Sentiment AnalysisCode1
General Debiasing for Multimodal Sentiment AnalysisCode0
ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis—0
Modality Influence in Multimodal Machine Learning—0
Towards Arabic Multimodal Dataset for Sentiment AnalysisCode0
Syntax-aware Hybrid prompt model for Few-shot multi-modal sentiment analysis—0
Denoising Bottleneck with Mutual Information Maximization for Video Multimodal FusionCode0
Cross-Attention is Not Enough: Incongruity-Aware Dynamic Hierarchical Fusion for Multimodal Affect RecognitionCode0
Speech-Text Dialog Pre-training for Spoken Dialog Understanding with Explicit Cross-Modal AlignmentCode0
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