Valence Classification on MAHNOB-HCI
85.49AccuracySiddharth et al. (2019)
Evaluation results
| Method | Links | |
|---|---|---|
| Siddharth et al. (2019)Modalities=Facial, Bio-Sensing, Features=Face appearance, PSD, Physiological image-based etc.2026.05 | 85.49 | |
| Zhu et al. (2024)Modalities=Facial, EEG, Features=Face appearance, PSD2026.05 | 79.37 | |
| Li et al. (2021)Modalities=Facial, EEG, Features=Face appearance, PSD2026.05 | 78.56 | |
| Oğuz et al. (2023)Modalities=ECG, Features=Morphological, HRV2026.05 | 78.28 | |
| SCPTModalities=Facial, rPPG, Features=Face appearance, rPPG deep learning-based2026.05 | 75.83 | |
| Wu et al. (2026)Modalities=Facial, EEG, Features=Face appearance, EEG deep learning-based2026.05 | 75.12 | |
| Mellouk et al. (2023)Modalities=rPPG, Features=rPPG deep learning-based2026.05 | 73.33 | |
| Tan et al. (2021)Modalities=Facial, EEG, Features=Facial landmarks, EEG deep learning-based2026.05 | 72.12 | |
| CAPModalities=Facial, rPPG, Features=Face appearance, rPPG deep learning-based2026.05 | 71.67 | |
| Ferdinando et al. (2018)Modalities=ECG, Features=HRV2026.05 | 70.7 | |
| CAModalities=Facial, rPPG, Features=Face appearance, rPPG deep learning-based2026.05 | 69.17 | |
| Li et al. (2024)Modalities=Facial, rPPG, Features=Face appearance, rPPG deep learning-based2026.05 | 68.54 | |
| Jia et al. (2024)Modalities=Bio-Sensing, Features=Bio-sensing deep learning-based2026.05 | 66 | |
| Singh et al. (2023)Modalities=Bio-Sensing, Features=Bio-sensing deep learning-based2026.05 | 65.44 | |
| Ali et al. (2025)Modalities=Facial, Bio-Sensing, Features=Face appearance, Physiological image-based2026.05 | 50.01 |