Face Verification

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.

( Image credit: Pose-Robust Face Recognition via Deep Residual Equivariant Mapping )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1–10 of 360 papers

Title	Date	Tasks	Status
ProxyFusion: Face Feature Aggregation Through Sparse Experts	Sep 24, 2025	Face IdentificationFace Recognition	CodeCode Available
DiffClean: Diffusion-based Makeup Removal for Accurate Age Estimation	Jul 17, 2025	Age EstimationFace Verification	—Unverified
50 Years of Automated Face Recognition	May 30, 2025	Face RecognitionFace Verification	—Unverified
Benchmarking Foundation Models for Zero-Shot Biometric Tasks	May 30, 2025	AttributeBenchmarking	—Unverified
Diffusion-based Adversarial Identity Manipulation for Facial Privacy Protection	Apr 30, 2025	Face RecognitionFace Verification	—Unverified
A Rapid Test for Accuracy and Bias of Face Recognition Technology	Feb 20, 2025	Face RecognitionFace Verification	CodeCode Available
Found in Translation: semantic approaches for enhancing AI interpretability in face verification	Jan 6, 2025	Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)	—Unverified
Sample Correlation for Fingerprinting Deep Face Recognition	Dec 30, 2024	Adversarial DefenseEmotion Recognition	CodeCode Available
ErasableMask: A Robust and Erasable Privacy Protection Scheme against Black-box Face Recognition Models	Dec 22, 2024	Adversarial AttackFace Recognition	—Unverified
VariFace: Fair and Diverse Synthetic Dataset Generation for Face Recognition	Dec 9, 2024	Dataset GenerationDiversity	—Unverified

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All datasets IJB-C IJB-A IJB-B MegaFace YouTube Faces DB BTS3.1 Labeled Faces in the Wild Trillion Pairs Dataset AgeDB-30 CFP-FP BUAA-VisNir CASIA NIR-VIS 2.0

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	WebFace42M baseline	TAR @ FAR=1e-4	97.7	—	Unverified
2	AdaFace (WebFace4M)	TAR @ FAR=1e-4	97.39	—	Unverified
3	FFC	TAR @ FAR=1e-4	97.31	—	Unverified
4	CAFace+AdaFace (WebFace4M)	TAR @ FAR=1e-4	97.3	—	Unverified
5	Partial FC	TAR @ FAR=1e-5	97.23	—	Unverified
6	AdaFace (MS1MV3)	TAR @ FAR=1e-4	97.09	—	Unverified
7	PartialFC	TAR @ FAR=1e-5	96.93	—	Unverified
8	AdaFace (MS1MV2)	TAR @ FAR=1e-4	96.89	—	Unverified
9	ElasticFace-Cos	TAR @ FAR=1e-4	96.57	—	Unverified
10	Arc+UNPG	TAR @ FAR=1e-4	96.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Dual-Agent GANs	TAR @ FAR=0.01	97.6	—	Unverified
2	PFEfuse + match	TAR @ FAR=0.01	97.5	—	Unverified
3	SE-GV-4-g1	TAR @ FAR=0.01	97.2	—	Unverified
4	L2-constrained softmax loss	TAR @ FAR=0.01	97	—	Unverified
5	VGGFace2_ft	TAR @ FAR=0.01	96.8	—	Unverified
6	StyleFNM	TAR @ FAR=0.01	94.6	—	Unverified
7	Deep Residual Equivariant Mapping	TAR @ FAR=0.01	94.4	—	Unverified
8	NAN	TAR @ FAR=0.01	94.1	—	Unverified
9	Template adaptation	TAR @ FAR=0.01	93.9	—	Unverified
10	All-in-one CNN	TAR @ FAR=0.01	92.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	QMagFace	TAR @ FAR=0.01	97.72	—	Unverified
2	Arc+UNPG	TAR @ FAR=0.01	97.7	—	Unverified
3	Mag+UNPG	TAR @ FAR=0.01	97.63	—	Unverified
4	Cos+UNPG	TAR @ FAR=0.01	97.36	—	Unverified
5	CAFace+AdaFace (WebFace4M)	TAR @ FAR=0.001	96.91	—	Unverified
6	PartialFC(WebFace42M)	TAR@FAR=0.0001	96.71	—	Unverified
7	FPN	TAR @ FAR=0.01	96.5	—	Unverified
8	SE-GV-3-g2	TAR @ FAR=0.01	96.4	—	Unverified
9	AdaFace (WebFace4M)	TAR@FAR=0.0001	96.03	—	Unverified
10	AdaFace (MS1MV3)	TAR@FAR=0.0001	95.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Prodpoly	Accuracy	98.95	—	Unverified
2	ElasticFace-Arc	Accuracy	98.81	—	Unverified
3	GhostFaceNetV2-1	Accuracy	98.72	—	Unverified
4	ArcFace + MS1MV2 + R100 + R	Accuracy	98.48	—	Unverified
5	DiscFace	Accuracy	97.44	—	Unverified
6	Dynamic AdaCos	Accuracy	97.41	—	Unverified
7	SV-AM-Softmax	Accuracy	97.38	—	Unverified
8	CosFace	Accuracy	96.65	—	Unverified
9	PFEfuse + match	Accuracy	92.51	—	Unverified
10	SphereFace (3-patch ensemble)	Accuracy	89.14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SeqFace, 1 ResNet-64	Accuracy	98.12	—	Unverified
2	ArcFace + MS1MV2 + R100,	Accuracy	98.02	—	Unverified
3	CosFace	Accuracy	97.6	—	Unverified
4	VGG-Face	Accuracy	97.4	—	Unverified
5	PFEfuse+match	Accuracy	97.36	—	Unverified
6	QAN	Accuracy	96.17	—	Unverified
7	Light CNN-29	Accuracy	95.54	—	Unverified
8	Git Loss	Accuracy	95.3	—	Unverified
9	FaceNet	Accuracy	95.12	—	Unverified
10	SphereFace	Accuracy	95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ProxyFusion (Adaface)	TAR @ FAR=0.01	0.69	—	Unverified
2	CoNAN (Adaface)	TAR @ FAR=0.01	0.56	—	Unverified
3	NAN (Adaface)	TAR @ FAR=0.01	0.54	—	Unverified
4	MCN (Adaface)	TAR @ FAR=0.01	0.54	—	Unverified
5	CAFace (Adaface)	TAR @ FAR=0.01	0.51	—	Unverified
6	MCN (Arcface)	TAR @ FAR=0.01	0.39	—	Unverified
7	NAN (Arcface)	TAR @ FAR=0.01	0.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ArcFace + MS1MV2 + R100,	Accuracy	99.83	—	Unverified
2	FaceNet	Accuracy	99.63	—	Unverified
3	Dlib	Accuracy	99.38	—	Unverified
4	VGG-Face	Accuracy	98.78	—	Unverified
5	DeepFace	Accuracy	98.37	—	Unverified
6	DeepID	Accuracy	97.05	—	Unverified
7	OpenFace	Accuracy	92.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SV-AM-Softmax	Accuracy	72.71	—	Unverified
2	AM-Softmax	Accuracy	61.61	—	Unverified
3	Arc-Softmax	Accuracy	57.45	—	Unverified
4	A-Softmax	Accuracy	43.76	—	Unverified
5	F-Softmax	Accuracy	37.14	—	Unverified
6	HM-Softmax	Accuracy	34.46	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PartialFC(R200)	Accuracy	0.99	—	Unverified
2	GhostFaceNetV2-1	Accuracy	0.99	—	Unverified
3	DiscFace	Accuracy	0.98	—	Unverified
4	VarGFaceNet	Accuracy	0.98	—	Unverified
5	VarGNet	Accuracy	0.97	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PartialFC (R200)	Accuracy	1	—	Unverified
2	QMagFace	Accuracy	0.99	—	Unverified
3	VarGFaceNet	Accuracy	0.99	—	Unverified
4	VarGNet	Accuracy	0.9	—	Unverified
5	QMagFace	Accuracy	0.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LightCNN-29 + DVG	TAR @ FAR=0.001	97.3	—	Unverified
2	DVR Wu et al. (2019)	TAR @ FAR=0.001	96.9	—	Unverified
3	W-CNN He et al. (2018)	TAR @ FAR=0.001	91.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LightCNN-29 + DVG	TAR @ FAR=0.001	99.8	—	Unverified
2	DVR Wu et al. (2019)	TAR @ FAR=0.001	99.6	—	Unverified
3	W-CNN He et al. (2018)	TAR @ FAR=0.001	98.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ArcFaceR50 + EM-FRR	BFAR	33.65	—	Unverified
2	ArcFaceR50 + EM-C	BFAR	2.44	—	Unverified
3	ArcFaceR50 + EM-FAR	BFAR	2.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LightCNN-29 + DVG	TAR @ FAR=0.001	92.9	—	Unverified
2	DVR Wu et al. (2019)	TAR @ FAR=0.001	84.9	—	Unverified
3	W-CNN He et al. (2018)	TAR @ FAR=0.001	54.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DiscFace	Accuracy	96.15	—	Unverified
2	SFace	Accuracy	93.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DiscFace	Accuracy	93.37	—	Unverified
2	SFace	Accuracy	91.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AdaFace+CSFM	Rank-1 (Video2Booking)	72.65	—	Unverified
2	ArcFace+CSFM	Rank-1 (Video2Booking)	65.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SphereFace	Accuracy	93.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LightCNN-29 + DVG	TAR @ FAR=0.01	97.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeepId2+	Accuracy	96.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DiscFace	TAR @ FAR=0.1	35.9	—	Unverified