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In recent years, Face Image Quality Assessment (FIQA) has become an indispensable part of the face recognition system to guarantee the stability and reliability of recognition performance in an unconstrained scenario.
Robust estimation of a location parameter
P. J. Huber · 1992
Earlier work this paper cites.
Probability, random variables, and stochastic processes
A. Papoulis and S. U. Pillai · 2002
Earlier work this paper cites.
Face recognition using laplacianfaces
X. He, S. Yan, Y. Hu, P. Niyogi, and H.-J. Zhang · 2005
Earlier work this paper cites.
Standardization of face image sample quality
X. Gao, S. Z. Li, R. Liu, and P. Zhang · 2007
Earlier work this paper cites.
Labeled faces in the wild: A database for studying face recognition in unconstrained environments
G. Huang, M. Mattar, T. Berg, and E. Learned-Miller · 2008
Earlier work this paper cites.
Image-quality-based adaptive face recognition
H. Sellahewa and S. A. Jassim · 2010
Earlier work this paper cites.
Predicting performance of face recognition systems: an image characterization approach
G. Aggarwal, S. Biswas, P. J. Flynn, and K. W. Bowyer · 2011
Earlier work this paper cites.
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
Earlier work this paper cites.
No-reference image quality assessment in the spatial domain
A. Mittal, A. K. Moorthy, and A. C. Bovik · 2012
Earlier work this paper cites.
Blind image quality assessment: A natural scene statistics approach in the dct domain
M. A. Saad, A. C. Bovik, and C. Charrier · 2012
Earlier work this paper cites.
Learning face representation from scratch
Y. Dong, Z. Lei, S. Liao, and S. Z. Stan · 2014
Earlier work this paper cites.
Age and gender estimation of unfiltered faces
E. Eidinger, R. Enbar, and T. 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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Face image assessment learned with objective and relative face image qualities for improved face recognition
H. Kim, S. H. Lee, and M. R. Yong · 2015
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Facenet: A unified embedding for face recognition and clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
Cited alongside, same era.
Iso/iec 29794-1:2016 information technology biometric sample quality — part 1: Framework
ISO/IEC · 2016
Cited alongside, same era.
Joint face detection and alignment using multitask cascaded convolutional networks
K. Zhang, Z. Zhang, Z. Li, and Y. Qiao · 2016
Blind image quality assessment with a probabilistic quality representation
H. Zeng, L. Zhang, and A. C. Bovik · 2018
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Arcface: Additive angular margin loss for deep face recognition
J. Deng, J. Guo, N. Xue, and S. Zafeiriou · 2019
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Faceqnet: Quality assessment for face recognition based on deep learning
J. Hernandez-Ortega, J. Galbally, J. Fierrez, R. Haraksim, and L. Beslay · 2019
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Probabilistic face embeddings
Y. Shi and A. K. Jain · 2019
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Biometric quality: review and application to face recognition with faceqnet
J. Hernandez-Ortega, J. Galbally, J. Fierrez, and L. Beslay · 2020
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Improving face recognition from hard samples via distribution distillation loss
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Assessing face image quality for smartphone based face recognition system
P. Wasnik, K. B. Raja, R. Ramachandra, and C. Busch · 2017
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Age progression/regression by conditional adversarial autoencoder
Z. Zhang, Y. Song, and H. Qi · 2017
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Learning face image quality from human assessments
L. Best-Rowden and A. K. Jain · 2018
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Iarpa janus benchmark - c: Face dataset and protocol
B. Maze, J. Adams, J. A. Duncan, N. Kalka, T. Miller, C. Otto, A. K. Jain, W. T. Niggel, J. Anderson, J. Cheney, and P. Grother · 2018
Cited alongside, same era.
Cosface: Large margin cosine loss for deep face recognition
H. Wang, Y. Wang, Z. Zhou, X. Ji, D. Gong, J. Zhou, Z. Li, and W. Liu · 2018
Cited alongside, same era.
Y. Huang, P. Shen, Y. Tai, S. Li, X. Liu, J. Li, F. Huang, and R. Ji · 2020
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Face image quality assessment: A literature survey
T. Schlett, C. Rathgeb, O. Henniger, J. Galbally, J. Fierrez, and C. Busch · 2020
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P. Terhörst, J. N. Kolf, N. Damer, F. Kirchbuchner, and A. Kuijper · 2020
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Ser-fiq: Unsupervised estimation of face image quality based on stochastic embedding robustness
P. Terhörst, J. N. Kolf, N. Damer, F. Kirchbuchner, and A. Kuijper · 2020
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Inducing predictive uncertainty estimation for face recognition
W. Xie, J. Byrne, and A. Zisserman · 2020
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