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Face recognition systems have to deal with large variabilities (such as different poses, illuminations, and expressions) that might lead to incorrect matching decisions.
The FERET evaluation methodology for face-recognition algorithms
P. Jonathon Phillips, Hyeonjoon Moon, Syed A. Rizvi, and Patrick J. Rauss · 2000
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Names and faces in the news
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Learning a similarity metric discriminatively, with application to face verification
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MORPH: A longitudinal image database of normal adult age-progression
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Standardization of face image sample quality
Xiufeng Gao, Stan Z. Li, Rong Liu, and Peiren Zhang · 2007
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Labeled faces in the wild: A database for studying face recognition in unconstrained environments
Gary B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller · 2007
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Image-quality-based adaptive face recognition
H. Sellahewa and S. A. Jassim · 2010
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Predicting performance of face recognition systems: An image characterization approach
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Standard, International Organization for Standardization, Nov. 2011
Information technology – Biometric data interchange formats – Part 5: Face image data · 2011
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Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition
Y. Wong, S. Chen, S. Mau, C. Sanderson, and B. C. Lovell · 2011
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Quality metrics for practical face recognition
A. Abaza, M. A. Harrison, and T. Bourlai · 2012
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Face image conformance to iso/icao standards in machine readable travel documents
M. Ferrara, A. Franco, D. Maio, and D. Maltoni · 2012
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On the existence of face quality measures
P. J. Phillips, J. R. Beveridge, D. S. Bolme, B. A. Draper, G. H. Givens, Y. M. Lui, S. Cheng, M. N. Teli, and H. Zhang · 2013
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Design and evaluation of photometric image quality measures for effective face recognition
A. Abaza, M. A. Harrison, T. Bourlai, and A. Ross · 2014
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A bayesian model for predicting face recognition performance using image quality
Abhishek Dutta, Raymond N. J. Veldhuis, and Luuk J. Spreeuwers · 2014
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Age and gender estimation of unfiltered faces
Eran Eidinger, Roee Enbar, and Tal Hassner · 2014
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Face image quality assessment based on learning to rank
J. Chen, Y. Deng, G. Bai, and G. Su · 2015
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Standard, International Civil Aviation Organization, 2015
Machine Readable Travel Documents · 2015
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Face image assessment learned with objective and relative face image qualities for improved face recognition
H. Kim, S. H. Lee, and Y. M. Ro · 2015
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Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin · 2015
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Ms-celeb-1m: A dataset and benchmark for large-scale face recognition
Yandong Guo, Lei Zhang, Yuxiao Hu, Xiaodong He, and Jianfeng Gao · 2016
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Standard, International Organization for Standardization, 2016
ISO/IEC 19795-1:2006 Information technology — Biometric performance testing and reporting · 2016
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Frontal to profile face verification in the wild
Soumyadip Sengupta, Jun-Cheng Chen, Carlos Domingo Castillo, Vishal M. Patel, Rama Chellappa, and David W. Jacobs · 2016
Cosface: Large margin cosine loss for deep face recognition
Hao Wang, Yitong Wang, Zheng Zhou, Xing Ji, Dihong Gong, Jingchao Zhou, Zhifeng Li, and Wei Liu · 2018
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Arcface: Additive angular margin loss for deep face recognition
Jiankang Deng, Jia Guo, Niannan Xue, and Stefanos Zafeiriou · 2019
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Faceqnet: Quality assessment for face recognition based on deep learning
Javier Hernandez-Ortega, Javier Galbally, Julian Fiérrez, Rudolf Haraksim, and Laurent Beslay · 2019
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Probabilistic face embeddings
Yichun Shi and Anil K. Jain · 2019
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Improved residual networks for image and video recognition
Ionut Cosmin Duta, Li Liu, Fan Zhu, and Ling Shao · 2020
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Curricularface: Adaptive curriculum learning loss for deep face recognition
Yuge Huang, Yuhan Wang, Ying Tai, Xiaoming Liu, Pengcheng Shen, Shaoxin Li, Jilin Li, and Feiyue Huang · 2020
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Sphereface: Deep hypersphere embedding for face recognition
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Quality aware network for set to set recognition
Yu Liu, Junjie Yan, and Wanli Ouyang · 2017
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Agedb: The first manually collected, in-the-wild age database
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Deep metric learning with angular loss
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IARPA janus benchmark-b face dataset
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Neural aggregation network for video face recognition
Jiaolong Yang, Peiran Ren, Dongqing Zhang, Dong Chen, Fang Wen, Hongdong Li, and Gang Hua · 2017
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Groupface: Learning latent groups and constructing group-based representations for face recognition
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Face quality estimation and its correlation to demographic and non-demographic bias in face recognition
Philipp Terhörst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, and Arjan Kuijper · 2020
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SER-FIQ: unsupervised estimation of face image quality based on stochastic embedding robustness
Philipp Terhörst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, and Arjan Kuijper · 2020
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Inducing predictive uncertainty estimation for face recognition
Weidi Xie, Jeffrey Byrne, and Andrew Zisserman · 2020
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Elasticface: Elastic margin loss for deep face recognition
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Eqface: A simple explicit quality network for face recognition
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Magface: A universal representation for face recognition and quality assessment
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Sdd-fiqa: Unsupervised face image quality assessment with similarity distribution distance
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A comprehensive study on face recognition biases beyond demographics
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