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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 101–150 of 202 papers

TitleStatusHype
Gated Mechanism for Attention Based Multimodal Sentiment Analysis—0
Generalizable Multi-linear Attention Network—0
Graph-based Fine-grained Multimodal Attention Mechanism for Sentiment Analysis—0
Hierarchical Adaptive Expert for Multimodal Sentiment Analysis—0
Highlight Timestamp Detection Model for Comedy Videos via Multimodal Sentiment Analysis—0
Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis—0
Improving Multimodal fusion via Mutual Dependency Maximisation—0
Improving Multimodal Sentiment Analysis: Supervised Angular Margin-based Contrastive Learning for Enhanced Fusion Representation—0
Improving the Modality Representation with Multi-View Contrastive Learning for Multimodal Sentiment Analysis—0
Large Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Survey—0
Learning in Order! A Sequential Strategy to Learn Invariant Features for Multimodal Sentiment Analysis—0
Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis—0
Learning Robust Joint Representations for Multimodal Sentiment Analysis—0
Lightweight Models for Multimodal Sequential Data—0
M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis—0
MART: Masked Affective RepresenTation Learning via Masked Temporal Distribution Distillation—0
Meta-Learn Unimodal Signals with Weak Supervision for Multimodal Sentiment Analysis—0
Missing Modality meets Meta Sampling (M3S): An Efficient Universal Approach for Multimodal Sentiment Analysis with Missing Modality—0
Modality Influence in Multimodal Machine Learning—0
Modality-Invariant Bidirectional Temporal Representation Distillation Network for Missing Multimodal Sentiment Analysis—0
Modeling Intra- and Inter-Modal Relations: Hierarchical Graph Contrastive Learning for Multimodal Sentiment Analysis—0
Multi-channel Attentive Graph Convolutional Network With Sentiment Fusion For Multimodal Sentiment Analysis—0
Multi-label Emotion Analysis in Conversation via Multimodal Knowledge Distillation—0
Multimodal Contrastive Learning via Uni-Modal Coding and Cross-Modal Prediction for Multimodal Sentiment Analysis—0
Multimodal fusion via cortical network inspired losses—0
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph—0
Multimodal Mixture of Low-Rank Experts for Sentiment Analysis and Emotion Recognition—0
Multimodal Representations Learning Based on Mutual Information Maximization and Minimization and Identity Embedding for Multimodal Sentiment Analysis—0
Multimodal Sentiment Analysis—0
Multimodal Sentiment Analysis: Addressing Key Issues and Setting up the Baselines—0
Polarity and Intensity: the Two Aspects of Sentiment Analysis—0
PowMix: A Versatile Regularizer for Multimodal Sentiment Analysis—0
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
StreaMulT: Streaming Multimodal Transformer for Heterogeneous and Arbitrary Long Sequential Data—0
Stronger Baseline for Robust Results in Multimodal Sentiment Analysis—0
Syntax-aware Hybrid prompt model for Few-shot multi-modal sentiment analysis—0
Targeted aspect based multimodal sentiment analysis:an attention capsule extraction and multi-head fusion network—0
TCAN: Text-oriented Cross Attention Network for Multimodal Sentiment Analysis—0
TextMI: Textualize Multimodal Information for Integrating Non-verbal Cues in Pre-trained Language Models—0
The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvements—0
TI-JEPA: An Innovative Energy-based Joint Embedding Strategy for Text-Image Multimodal Systems—0
Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning—0
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