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SotA/Computer Vision/Face Verification

Face Verification

44 benchmarks360 papers

Face Verification is a machine learning task in computer vision that involves determining whether two facial images belong to the same person or not. The task involves extracting features from the facial images, such as the shape and texture of the face, and then using these features to compare and verify the similarity between the images.

<span style="color:grey; opacity: 0.6">( Image credit: Pose-Robust Face Recognition via Deep Residual Equivariant Mapping )</span>

Benchmarks

Face Verification on IJB-B

TAR@FAR=0.0001TAR @ FAR=0.001TAR @ FAR=1e-5TAR @ FAR=0.0001TAR @ FAR=0.01

Face Verification on BTS3.1

TAR @ FAR=0.01

Face Verification on Trillion Pairs Dataset

Accuracy

Face Verification on AgeDB-30

Accuracy

Face Verification on CFP-FP

Accuracy

Face Verification on IJB-C

TAR @ FAR=1e-3TAR @ FAR=1e-2Rank-1Rank-5TAR @ FAR=1e-6TAR @ FAR=1e-5TAR @ FAR=1e-4training datasetmodel

Face Verification on BUAA-VisNir

TAR @ FAR=0.001TAR @ FAR=0.01

Face Verification on CASIA NIR-VIS 2.0

TAR @ FAR=0.001

Face Verification on IJB-A

TAR @ FAR=0.001TAR @ FAR=0.1TAR @ FAR=0.01

Face Verification on LFW

BFARBFRRFRR@FAR(%)

Face Verification on Oulu-CASIA NIR-VIS

TAR @ FAR=0.001TAR @ FAR=0.01

Face Verification on Disguised Faces in the Wild

GAR @0.1% FARGAR @1% FARGAR @10% FAR

Face Verification on IJB-S

Rank-1 (Video2Booking)Rank-1 (Video2Single)Rank-1 (Video2Video)

Face Verification on CALFW

Accuracy

Face Verification on CK+

Accuracy

Face Verification on CPLFW

Accuracy

Face Verification on IIIT-D Viewed Sketch

TAR @ FAR=0.01

Face Verification on MegaFace

Accuracy

Face Verification on Oulu-CASIA

Accuracy

Face Verification on QMUL-SurvFace

TAR @ FAR=0.1

Face Verification on Labeled Faces in the Wild

Accuracy

Face Verification on YouTube Faces DB

Accuracy