Emotion Recognition on DEAP (Valence/Arousal Accuracy)
97.84Valence AccuracyMilmer
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| MilmerModality=Multimodal, Class=22025.02 | 97.84 | 97.91 | — | |
| Hosseini et al. (2024)Modality=EEG+Face, Class=22025.02 | 97.39 | 97.79 | — | |
| Wang et al. (2023)Modality=EEG+Face, Class=22025.02 | 96.63 | 97.15 | — | |
| Wu and Li (2023)Modality=EEG+Face, Class=22025.02 | 95.3 | 94.94 | — | |
| Wang et al. (2025)Modality=EEG+Face, Class=22025.02 | 86.75 | 83.24 | — | |
| Zhao et al. (2021)Modality=EEG+Face, Class=22025.02 | 86.2 | 86.8 | — | |
| Salama et al. (2018)Modality=EEG, Class=22025.02 | 86 | 87.97 | — | |
| Huang et al. (2019)Modality=EEG+Face, Class=22025.02 | 80.3 | 74.23 | — | |
| Siddharth et al.Modalities=Facial, EEG, Features=Face appearance, PSD2026.05 | 79.52 | 78.34 | — | |
| Jung et al. (2019)Modality=EEG+Face, Class=22025.02 | 79.52 | 78.34 | — | |
| Wu et al.Modalities=Facial, EEG, Features=Face appearance, EEG deep learning-based2026.05 | 72.89 | 71.71 | — | |
| Zhu et al.Modalities=Facial, EEG, Features=Face appearance, PSD2026.05 | 72.22 | 70.69 | — | |
| Siddharth et al.Modalities=Bio-sensing, Features=PSD, Physiological image-based etc.2026.05 | 71.87 | 73.05 | — | |
| Elalamy et al.Modalities=Bio-Sensing, Features=Physiological image-based2026.05 | 69.9 | 69.7 | — | |
| Li et al.Modalities=Bio-Sensing, Features=Bio-sensing deep learning-based2026.05 | 69.62 | 70.62 | — | |
| SCPTModalities=Facial, rPPG, Features=Face appearance, rPPG deep learning-based2026.05 | 67.92 | 65.41 | — | |
| Tan et al.Modalities=Facial, EEG, Features=Facial landmarks, EEG deep learning-based2026.05 | 67.76 | 78.97 | — | |
| Gao et al.Modalities=Facial, Bio-Sensing, Features=Face appearance, EEG&ECG deep learning-based2026.05 | 65.84 | 64.62 | — | |
| Wu et al. (2023)Modality=EEG+Face, Class=22025.02 | 64.77 | 72.73 | — | |
| CAPModalities=Facial, rPPG, Features=Face appearance, rPPG deep learning-based, Fusion=Direct Concatenation-Projection2026.05 | 63.75 | 62.92 | — | |
| CAModalities=Facial, rPPG, Features=Face appearance, rPPG deep learning-based, Fusion=Cross-Attention2026.05 | 62.5 | 61.25 | — | |
| Jia et al.Modalities=Bio-Sensing, Features=Bio-sensing deep learning-based2026.05 | 61.5 | 65.3 | — | |
| Li et al.Modalities=Facial, rPPG, Features=Face appearance, rPPG deep learning-based2026.05 | 61.25 | 63.75 | — | |
| Tian et al.Modalities=Bio-Sensing, Features=Bio-sensing deep learning-based2026.05 | 60.07 | 64.16 | — | |
| Wu et al.Modalities=Facial, rPPG, Features=Face appearance, rHRV deep learning-based2026.05 | 60 | 72.5 | — | |
| Romeo et al. (2019)Modality=EEG, Class=22025.02 | 54.6 | 61.1 | — | |
| DLinearEvaluation Protocol=Cross-Subject2026.07 | — | — | 72.6 | |
| InformerEvaluation Protocol=Cross-Subject2026.07 | — | — | 69.31 | |
| iTransformerEvaluation Protocol=Cross-Subject2026.07 | — | — | 65.97 | |
| NTransformerEvaluation Protocol=Cross-Subject2026.07 | — | — | 69.08 | |
| PRISMEvaluation Protocol=Cross-Subject2026.07 | — | — | 87.45 | |
| TCNEvaluation Protocol=Cross-Subject2026.07 | — | — | 79.12 | |
| TimesNetEvaluation Protocol=Cross-Subject2026.07 | — | — | 77.76 |