Lightweight Face Recognition On Agedb 30
Métriques
Accuracy
MParams
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | MParams | Paper Title | Repository |
|---|---|---|---|---|
| Seesaw-shuffleFaceNet(mobi) | 0.9648 | 2.8 | SeesawFaceNets: sparse and robust face verification model for mobile platform | |
| EdgeFace - XS (g=0.6) | 0.96 | 1.77 | EdgeFace: Efficient Face Recognition Model for Edge Devices | |
| EdgeFace - S (g=0.5) | 0.9693 | 3.65 | EdgeFace: Efficient Face Recognition Model for Edge Devices | |
| MobileFaceNet | 0.9305 | - | MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices | |
| PocketNetS | 0.9635 | - | PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge Distillation |
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