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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 31–40 of 180 papers

Title	Date	Tasks	Status	Hype
Hierarchical Hypercomplex Network for Multimodal Emotion Recognition	Sep 13, 2024	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	2
Early Joint Learning of Emotion Information Makes MultiModal Model Understand You Better	Sep 12, 2024	Emotion RecognitionLanguage Modeling	—Unverified	0
Recent Trends of Multimodal Affective Computing: A Survey from NLP Perspective	Sep 11, 2024	Aspect-Based Sentiment AnalysisEmotion Recognition	CodeCode Available	2
Multimodal Emotion Recognition with Vision-language Prompting and Modality Dropout	Sep 11, 2024	Emotion RecognitionMultimodal Emotion Recognition	—Unverified	0
Leveraging Contrastive Learning and Self-Training for Multimodal Emotion Recognition with Limited Labeled Samples	Aug 23, 2024	Contrastive LearningEmotion Recognition	CodeCode Available	0
Video Emotion Open-vocabulary Recognition Based on Multimodal Large Language Model	Aug 21, 2024	Emotion RecognitionLanguage Modeling	—Unverified	0
SZTU-CMU at MER2024: Improving Emotion-LLaMA with Conv-Attention for Multimodal Emotion Recognition	Aug 20, 2024	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	4
Enhancing Modal Fusion by Alignment and Label Matching for Multimodal Emotion Recognition	Aug 18, 2024	Contrastive LearningEmotion Recognition	CodeCode Available	1
Multi Teacher Privileged Knowledge Distillation for Multimodal Expression Recognition	Aug 16, 2024	Emotion RecognitionKnowledge Distillation	CodeCode Available	0
Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion Recognition	Jul 31, 2024	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1

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All datasets IEMOCAP-4 MELD IEMOCAP CMU-MOSEI-Sentiment CMU-MOSEI-Sentiment-3 Expressive hands and faces dataset (EHF).MELD-Sentiment

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	86.52	—	Unverified
2	Joyful	Weighted F1	85.7	—	Unverified
3	COGMEN	Weighted F1	84.5	—	Unverified
4	DANN	Accuracy	82.7	—	Unverified
5	MMER	Accuracy	81.7	—	Unverified
6	PATHOSnet v2	Accuracy	80.4	—	Unverified
7	Self-attention weight correction (A+T)	Accuracy	76.8	—	Unverified
8	CHFusion	Accuracy	76.5	—	Unverified
9	bc-LSTM	Weighted F1	74.1	—	Unverified
10	Audio + Text (Stage III)	F1	70.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	66.71	—	Unverified
2	Audio + Text (Stage III)	Weighted F1	65.8	—	Unverified
3	Joyful	Weighted F1	61.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	72.81	—	Unverified
2	Joyful	Weighted F1	70.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	44.93	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	66.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SMPLify-X	v2v error	52.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	74.31	—	Unverified