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Face Recognition On Lfw

Metrics

Accuracy

Results

Performance results of various models on this benchmark

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