Facial Expression Recognition On Fer 1
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy |
|---|---|
| a-dual-direction-attention-mixed-feature | 90.74 |
| facial-expression-recognition-using-vanilla | 88.91 |
| facial-expression-recognition-with-grid-wise | 90.04 |
| exploring-emotion-features-and-fusion | 89.257 |
| efficient-facial-feature-learning-with-wide | 87.15 |
| learn-from-all-erasing-attention-consistency | 89.64 |
| qcs-feature-refining-from-quadruplet-cross | 91.85 |
| facial-expression-recognition-using-vanilla | 90.18 |
| facial-expression-recognition-using-vanilla | 88.56 |
| real-time-emotion-analysis-using-deep | 91.41 |
| grefel-geometry-aware-reliable-facial | 93.09 |
| adaptively-learning-facial-expression-1 | 90.49 |
| local-learning-with-deep-and-handcrafted | 87.76 |
| patt-lite-lightweight-patch-and-attention | 95.55 |