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	Score
GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognition	Dec 7, 2023	Emotion RecognitionFacial Emotion Recognition	CodeCode Available	1	5
Curriculum Learning Meets Directed Acyclic Graph for Multimodal Emotion Recognition	Feb 27, 2024	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1	5
A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party Conversations	Jul 1, 2023	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1	5
Decoupled Multimodal Distilling for Emotion Recognition	Mar 24, 2023	Emotion RecognitionKnowledge Distillation	CodeCode Available	1	5
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	5
A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in Conversations	Oct 31, 2023	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1	5
Cooperative Sentiment Agents for Multimodal Sentiment Analysis	Apr 19, 2024	DisentanglementEmotion Recognition	CodeCode Available	1	5
Cross Attentional Audio-Visual Fusion for Dimensional Emotion Recognition	Nov 9, 2021	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	1	5
A proposal for Multimodal Emotion Recognition using aural transformers and Action Units on RAVDESS dataset	Dec 30, 2021	Autonomous DrivingEmotion Recognition	CodeCode Available	1	5
DialogueRNN: An Attentive RNN for Emotion Detection in Conversations	Nov 1, 2018	Emotion ClassificationEmotion Recognition in Conversation	CodeCode Available	1	5

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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