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Face Verification On Ijb C

Metriken

TAR @ FAR=1e-3
TAR @ FAR=1e-4
TAR @ FAR=1e-5
model
training dataset

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Vergleichstabelle
ModellnameTAR @ FAR=1e-3TAR @ FAR=1e-4TAR @ FAR=1e-5modeltraining dataset
circle-loss-a-unified-perspective-of-pair96.29%93.95%89.60%R100MS1M Cleaned
elasticface-elastic-margin-loss-for-deep-face-96.57%-R100MS1M V2
magface-a-universal-representation-for-face-95.97%90.36%R100MS1MV2
unified-negative-pair-generation-toward-well--94.7%--
arcface-additive-angular-margin-loss-for-deep--96.07%R100IBUG-500K
facenet-a-unified-embedding-for-face-----
killing-two-birds-with-one-stone-efficient-97.97%96.93%R200WebFace42M
rectifying-the-data-bias-in-knowledge97.05%95.49%93.25%MobileFaceNetMS1M V3
cluster-and-aggregate-face-recognition-with98.0897.3%---
probabilistic-face-embeddings95.49%--SphereFace64MS1M V2
an-efficient-training-approach-for-very-large-97.31%-R100WebFace42M
controllable-and-guided-face-synthesis-for-95.9%94.06%--
it-s-all-in-the-head-representation-knowledge-95.48%93.50%MobileFaceNetMS1M V3
multicolumn-networks-for-face-recognition-----
adaface-quality-adaptive-margin-for-face-97.39%---
webface260m-a-benchmark-unveiling-the-power-97.7%-R100WebFace42M
adaface-quality-adaptive-margin-for-face-97.09%---
curricularface-adaptive-curriculum-learning-96.1%---
qmagface-simple-and-accurate-quality-aware97.6296.19%---
unified-negative-pair-generation-toward-well97.5796.38%94.47%R100MS1MV2
killing-two-birds-with-one-stone-efficient-98.00%97.23%ViT-LWebFace42M
adaface-quality-adaptive-margin-for-face-96.89%---
look-across-elapse-disentangled-----
vggface2-a-dataset-for-recognising-faces92.7%--R50Vggface2
it-s-all-in-the-head-representation-knowledge-95.64%93.73%MobileFaceNetMS1M V3
unified-negative-pair-generation-toward-well97.5196.33%---