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Face Recognition On Lfw

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Model Name
Accuracy
Paper TitleRepository
DCQ0.998Dynamic Class Queue for Large Scale Face Recognition In the Wild
EdgeFace - S (g=0.5)0.9978EdgeFace: Efficient Face Recognition Model for Edge Devices
AdaFace + WebFace4M + R1000.9980AdaFace: Quality Adaptive Margin for Face Recognition
PIC - QMagFace-PIC-Score: Probabilistic Interpretable Comparison Score for Optimal Matching Confidence in Single- and Multi-Biometric (Face) Recognition
FaceTransformer+OctupletLoss0.9973Octuplet Loss: Make Face Recognition Robust to Image Resolution
PIC - ArcFace-PIC-Score: Probabilistic Interpretable Comparison Score for Optimal Matching Confidence in Single- and Multi-Biometric (Face) Recognition
QMagFace0.9850QMagFace: Simple and Accurate Quality-Aware Face Recognition
CircleLoss0.9973Circle Loss: A Unified Perspective of Pair Similarity Optimization
EdgeFace - XS (g=0.6)0.9973EdgeFace: Efficient Face Recognition Model for Edge Devices
OcularAI-Face0.945MagicEye: An Intelligent Wearable Towards Independent Living of Visually Impaired
PIC - MagFace-PIC-Score: Probabilistic Interpretable Comparison Score for Optimal Matching Confidence in Single- and Multi-Biometric (Face) Recognition
ArcFace + MS1MV2 + R1000.9983AdaFace: Quality Adaptive Margin for Face Recognition
SymFace + AdaFace + ResNet100 +WebFace (MS1MV2)0.9985SymFace: Additional Facial Symmetry Loss for Deep Face Recognition-
Prodpoly0.99833Deep Polynomial Neural Networks
GhostFaceNetV2-1 (MS1MV3)0.998667GhostFaceNets: Lightweight Face Recognition Model From Cheap Operations
DiscFace0.9983DiscFace: Minimum Discrepancy Learning for Deep Face Recognition-
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