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аналитика - Multimodal Emotion Analysis
Multimodal Emotion-Cause Pair Extraction in Conversations with Specialized Emotion Encoders and Multimodal Language Models
The MER-MCE framework leverages specialized emotion encoders for text, audio, and visual modalities, as well as Multimodal Language Models, to effectively identify emotions and their underlying causes in multimodal conversational data.
Unified Multimodal Framework for Emotion Recognition and Emotion-Cause Analysis
UniMEEC proposes a unified framework to jointly model emotion recognition and emotion-cause pair extraction, leveraging the complementarity and causality between emotion and emotion cause.
MSEVA: A System for Multimodal Short Videos Emotion Visual Analysis
Short videos' affective computing was neglected in the past, MSEVA system aims to monitor emotions in short videos for public opinion guidance.
JMI at SemEval 2024 Task 3: Two-step approach for multimodal ECAC using in-context learning with GPT and instruction-tuned Llama models
提案されたアプローチは、多様なモダリティを統合した効率的なマルチモーダル感情原因分析（ECA）システムの開発に取り組んでいます。
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