SOTAVerified

Multimodal Emotion Recognition

This is a leaderboard for multimodal emotion recognition on the IEMOCAP dataset. The modality abbreviations are A: Acoustic T: Text V: Visual

Please include the modality in the bracket after the model name.

All models must use standard five emotion categories and are evaluated in standard leave-one-session-out (LOSO). See the papers for references.

Papers

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Showing 1–10 of 180 papers

TitleStatusHype
A Robust Incomplete Multimodal Low-Rank Adaptation Approach for Emotion Recognition—0
GSDNet: Revisiting Incomplete Multimodal-Diffusion from Graph Spectrum Perspective for Conversation Emotion Recognition—0
Towards Robust Multimodal Emotion Recognition under Missing Modalities and Distribution ShiftsCode1
Multimodal Mixture of Low-Rank Experts for Sentiment Analysis and Emotion Recognition—0
TACFN: Transformer-based Adaptive Cross-modal Fusion Network for Multimodal Emotion RecognitionCode0
PsyCounAssist: A Full-Cycle AI-Powered Psychological Counseling Assistant System—0
Leveraging Label Potential for Enhanced Multimodal Emotion Recognition—0
BeMERC: Behavior-Aware MLLM-based Framework for Multimodal Emotion Recognition in Conversation—0
Unimodal-driven Distillation in Multimodal Emotion Recognition with Dynamic Fusion—0
GatedxLSTM: A Multimodal Affective Computing Approach for Emotion Recognition in Conversations—0
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All datasetsIEMOCAP-4MELDIEMOCAPCMU-MOSEI-SentimentCMU-MOSEI-Sentiment-3Expressive hands and faces dataset (EHF).MELD-Sentiment

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F166.73—Unverified