Drowsiness Estimation on FatigueView
94.41AccuracyHST-HGN
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| HST-HGNTraining dataset=YawDD, Protocol=Cross-dataset evaluation (backbone frozen, head adapted)2026.04 | 94.41 | 94.08 | — | — | |
| LiteFatTraining dataset=YawDD, Protocol=Cross-dataset evaluation (backbone frozen, head adapted)2026.04 | 93.79 | 93.26 | — | — | |
| JHPFA-NetTraining dataset=YawDD, Protocol=Cross-dataset evaluation (backbone frozen, head adapted)2026.04 | 93.17 | 92.81 | — | — | |
| IsoSSL-MoCoTraining dataset=YawDD, Protocol=Cross-dataset evaluation (backbone frozen, head adapted)2026.04 | 92.55 | 92.22 | — | — | |
| VBFLLFATraining dataset=YawDD, Protocol=Cross-dataset evaluation (backbone frozen, head adapted)2026.04 | 90.68 | 90.43 | — | — | |
| SlowFastTraining dataset=YawDD, Protocol=Cross-dataset evaluation (backbone frozen, head adapted)2026.04 | 90.06 | 89.73 | — | — | |
| VideoMAETraining dataset=YawDD, Protocol=Cross-dataset evaluation (backbone frozen, head adapted)2026.04 | 89.44 | 87.87 | — | — | |
| ResNet3D+2024.10 | 89.37 | 93.78 | 94.79 | 91.3 | |
| VDMoElosses=Ldrow only2024.10 | 87.7 | 92.91 | 95.03 | 90.4 | |
| 2s ST-GCNTraining dataset=YawDD, Protocol=Cross-dataset evaluation (backbone frozen, head adapted)2026.04 | 87.58 | 86.8 | — | — | |
| IsoSSL-MoCo+2024.10 | 86.77 | 88.35 | 91.44 | 86.77 | |
| VBFLFFA2024.10 | 86.51 | 92.33 | 95.21 | 87.02 | |
| ReNeXt3D-101+LSTM+2024.10 | 84.32 | 87.6 | 89.33 | 82.22 | |
| DDDNet+2024.10 | 83.2 | 86.66 | 89.12 | 83.05 | |
| ViViT+2024.10 | 82.9 | 90.7 | 83.44 | 88.62 | |
| FacialUnits2024.10 | 81.22 | 89.27 | 89.77 | 85.3 | |
| 2s-STGCN2024.10 | 80.44 | 86.71 | 90.04 | 84.28 | |
| MIGCN+2024.10 | 80.37 | 82.33 | 88.52 | 82.34 | |
| DBN-HMM+2024.10 | 79.35 | 81.66 | 86.35 | 80.61 | |
| 3DCNN+BiLSTM+2024.10 | 79.21 | 81.03 | 85.4 | 80.27 |