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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 61–70 of 202 papers

TitleStatusHype
MuSe 2020 -- The First International Multimodal Sentiment Analysis in Real-life Media Challenge and WorkshopCode1
Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in ConversationCode1
CAtCh: Cognitive Assessment through Cookie ThiefCode0
An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability—0
Multimodal Mixture of Low-Rank Experts for Sentiment Analysis and Emotion Recognition—0
Multimodal Sentiment Analysis on CMU-MOSEI Dataset using Transformer-based Models—0
Rethinking Multimodal Sentiment Analysis: A High-Accuracy, Simplified Fusion Architecture—0
Multimodal Transformers are Hierarchical Modal-wise Heterogeneous Graphs—0
Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysis—0
DeepMLF: Multimodal language model with learnable tokens for deep fusion in sentiment analysis—0
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