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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 131–140 of 202 papers

TitleStatusHype
PTA: Enhancing Multimodal Sentiment Analysis through Pipelined Prediction and Translation-based Alignment—0
Rethinking Multimodal Sentiment Analysis: A High-Accuracy, Simplified Fusion Architecture—0
RNG: Reducing Multi-level Noise and Multi-grained Semantic Gap for Joint Multimodal Aspect-Sentiment Analysis—0
Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation—0
ScaleVLAD: Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors—0
Seek Common Ground While Reserving Differences: Semi-Supervised Image-Text Sentiment Recognition—0
Sentiment Analysis of Fashion Related Posts in Social Media—0
Seq2Seq2Sentiment: Multimodal Sequence to Sequence Models for Sentiment Analysis—0
Shared and Private Information Learning in Multimodal Sentiment Analysis with Deep Modal Alignment and Self-supervised Multi-Task Learning—0
Speech-Text Dialog Pre-training for Spoken Dialog Understanding with Explicit Cross-Modal Alignment—0
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