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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 180 papers

TitleStatusHype
Joyful: Joint Modality Fusion and Graph Contrastive Learning for Multimodal Emotion RecognitionCode1
Conversation Understanding using Relational Temporal Graph Neural Networks with Auxiliary Cross-Modality InteractionCode1
A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in ConversationsCode1
Hypercomplex Multimodal Emotion Recognition from EEG and Peripheral Physiological SignalsCode1
CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion RecognitionCode1
A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party ConversationsCode1
Decoupled Multimodal Distilling for Emotion RecognitionCode1
Multimodal Information Bottleneck: Learning Minimal Sufficient Unimodal and Multimodal RepresentationsCode1
Exploiting modality-invariant feature for robust multimodal emotion recognition with missing modalitiesCode1
FV2ES: A Fully End2End Multimodal System for Fast Yet Effective Video Emotion Recognition InferenceCode1
GA2MIF: Graph and Attention Based Two-Stage Multi-Source Information Fusion for Conversational Emotion DetectionCode1
Multimodal Emotion Recognition with Modality-Pairwise Unsupervised Contrastive LossCode1
GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion RecognitionCode1
COGMEN: COntextualized GNN based Multimodal Emotion recognitioNCode1
MMER: Multimodal Multi-task Learning for Speech Emotion RecognitionCode1
A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion RecognitionCode1
Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responsesCode1
Group Gated Fusion on Attention-based Bidirectional Alignment for Multimodal Emotion RecognitionCode1
A proposal for Multimodal Emotion Recognition using aural transformers and Action Units on RAVDESS datasetCode1
Shapes of Emotions: Multimodal Emotion Recognition in Conversations via Emotion ShiftsCode1
Cross Attentional Audio-Visual Fusion for Dimensional Emotion RecognitionCode1
A cross-modal fusion network based on self-attention and residual structure for multimodal emotion recognitionCode1
Multimodal Emotion Recognition with High-level Speech and Text FeaturesCode1
MSAF: Multimodal Split Attention FusionCode1
Multimodal Emotion Recognition with Transformer-Based Self Supervised Feature FusionCode1
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All datasetsIEMOCAP-4MELDIEMOCAPCMU-MOSEI-SentimentCMU-MOSEI-Sentiment-3Expressive hands and faces dataset (EHF).MELD-Sentiment

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F186.52—Unverified
2JoyfulWeighted F185.7—Unverified
3COGMENWeighted F184.5—Unverified
4DANNAccuracy82.7—Unverified
5MMERAccuracy81.7—Unverified
6PATHOSnet v2Accuracy80.4—Unverified
7Self-attention weight correction (A+T)Accuracy76.8—Unverified
8CHFusionAccuracy76.5—Unverified
9bc-LSTMWeighted F174.1—Unverified
10Audio + Text (Stage III)F170.5—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F166.71—Unverified
2Audio + Text (Stage III)Weighted F165.8—Unverified
3JoyfulWeighted F161.77—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F172.81—Unverified
2JoyfulWeighted F170.5—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F144.93—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F166.73—Unverified
#ModelMetricClaimedVerifiedStatus
1SMPLify-Xv2v error52.9—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F174.31—Unverified