Multimodal Emotion Recognition on CREMA-D
77.02AccuracyDMIL
Evaluation results
| Method | Links | ||
|---|---|---|---|
| DMILBackbone=ResNet182026.06 | 77.02 | 85.13 | |
| MCRBackbone=ResNet182026.06 | 76.34 | 84.59 | |
| MLBBackbone=ResNet182026.06 | 75.94 | 83.83 | |
| EnsembleBackbone=ResNet182026.06 | 74.87 | 82.35 | |
| FCLBackbone=ResNet182026.06 | 74.73 | 83.08 | |
| MMIBBackbone=ResNet182026.06 | 74.59 | 83.23 | |
| MMMLBackbone=ResNet182026.06 | 74.46 | 83.03 | |
| I2M2Backbone=ResNet182026.06 | 74.13 | 82.9 | |
| AGMBackbone=ResNet182026.06 | 73.51 | 82.17 | |
| MMTMBackbone=ResNet182026.06 | 73.44 | 82.08 | |
| QMFBackbone=ResNet182026.06 | 73.32 | 81.16 | |
| OGMBackbone=ResNet182026.06 | 72.95 | 80.67 | |
| JointBackbone=ResNet182026.06 | 72.55 | 81.12 | |
| PMRBackbone=ResNet182026.06 | 72.45 | 81.14 |