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 101–110 of 180 papers

Title	Date	Tasks	Status	Hype
CSAT‑FTCN: A Fuzzy‑Oriented Model with Contextual Self‑attention Network for Multimodal Emotion Recognition	Jan 31, 2023	Emotion RecognitionMultimodal Emotion Recognition	—Unverified	0
Seamless Multimodal Biometrics for Continuous Personalised Wellbeing Monitoring	Jan 8, 2023	Emotion RecognitionFace Recognition	—Unverified	0
Emotion Recognition with Pre-Trained Transformers Using Multimodal Signals	Dec 22, 2022	Emotion RecognitionMultimodal Emotion Recognition	—Unverified	0
Multimodal Emotion Recognition among Couples from Lab Settings to Daily Life using Smartwatches	Dec 21, 2022	Emotion RecognitionManagement	—Unverified	0
FAF: A novel multimodal emotion recognition approach integrating face, body and text	Nov 20, 2022	Emotion RecognitionMultimodal Emotion Recognition	—Unverified	0
Speech Emotion Recognition Based on Self-Attention Weight Correction for Acoustic and Text Features	Nov 8, 2022	Emotion RecognitionMultimodal Emotion Recognition	—Unverified	0
Multimodal Information Bottleneck: Learning Minimal Sufficient Unimodal and Multimodal Representations	Oct 31, 2022	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	1
Exploiting modality-invariant feature for robust multimodal emotion recognition with missing modalities	Oct 27, 2022	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	1
Multilevel Transformer For Multimodal Emotion Recognition	Oct 26, 2022	Emotion RecognitionMultimodal Emotion Recognition	—Unverified	0
FV2ES: A Fully End2End Multimodal System for Fast Yet Effective Video Emotion Recognition Inference	Sep 21, 2022	Emotion RecognitionMultimodal Emotion Recognition	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