Facial Recognition and Modelling on CASIA-WebFace+masks

Metric: Accuracy (higher is better)

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#	Model↕	Accuracy▼	Extra Data	Paper	Date↕	Code
1	Fine-tuned ArcFace	91.47	No	A realistic approach to generate masked faces ap...	2021-09-03	Code
2	Fine-tuned FaceNet	88.06	No	A realistic approach to generate masked faces ap...	2021-09-03	Code
3	ArcFace	87.95	Yes	ArcFace: Additive Angular Margin Loss for Deep F...	2018-01-23	Code
4	Fine-tuned VGG-Face	86.85	No	A realistic approach to generate masked faces ap...	2021-09-03	Code
5	FaceNet	84.21	No	FaceNet: A Unified Embedding for Face Recognitio...	2015-03-12	Code
6	VGG-Face	79.65	No	-	-	Code

#1Fine-tuned ArcFaceSOTA
91.47
Accuracy· 2021-09-03
A realistic approach to generate masked faces applied on two novel masked face recognition data sets Code
#2Fine-tuned FaceNet
88.06
Accuracy· 2021-09-03
A realistic approach to generate masked faces applied on two novel masked face recognition data sets Code
#3ArcFaceSOTA
87.95
Accuracy· Extra Data· 2018-01-23
ArcFace: Additive Angular Margin Loss for Deep Face Recognition Code
#4Fine-tuned VGG-Face
86.85
Accuracy· 2021-09-03
A realistic approach to generate masked faces applied on two novel masked face recognition data sets Code
#5FaceNetSOTA
84.21
Accuracy· 2015-03-12
FaceNet: A Unified Embedding for Face Recognition and Clustering Code
#6VGG-Face
79.65
Accuracy
No paperCode