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Face Verification On Ijb B

Métriques

TAR @ FAR=0.001
TAR @ FAR=0.01
TAR@FAR=0.0001

Résultats

Résultats de performance de divers modèles sur ce benchmark

Paper Title
PartialFC(WebFace42M)--96.71Killing Two Birds with One Stone:Efficient and Robust Training of Face Recognition CNNs by Partial FC
AdaFace (WebFace4M)--96.03AdaFace: Quality Adaptive Margin for Face Recognition
AdaFace (MS1MV3)--95.84AdaFace: Quality Adaptive Margin for Face Recognition
AdaFace (MS1MV2)--95.67AdaFace: Quality Adaptive Margin for Face Recognition
CAFace+AdaFace (WebFace4M)96.91-95.53Cluster and Aggregate: Face Recognition with Large Probe Set
Mag+UNPG96.597.63%95.21Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition
Arc+UNPG96.697.7%95.04Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition
Cos+UNPG96.597.36%94.99Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition
QMagFace96.4897.72%94.7QMagFace: Simple and Accurate Quality-Aware Face Recognition
SE-GV-3-g2-96.4%-GhostVLAD for set-based face recognition
VGGFace2_ft90.895.6%-VGGFace2: A dataset for recognising faces across pose and age
FPN-96.5%-FacePoseNet: Making a Case for Landmark-Free Face Alignment
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Face Verification On Ijb B | SOTA | HyperAI