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Face recognition has achieved outstanding performance in the last decade with the development of deep learning techniques.
The development of children ages 6 to 14
Jacquelynne Eccles · 1999
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Classifying adults’ and children’s faces by sex: computational investigations of subcategorical feature encoding
Yi D. Cheng, Alice J. O’Toole, and Hervé Abdi · 2001
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The use of children in the production, sales and trafficking of drugs: A synthesis of participatory action-oriented research programs in Indonesia, the Philippines and Thailand
Emma Porio and Christine S. Crisol · 2004
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Learning a similarity metric discriminatively, with application to face verification
Sumit Chopra, Raia Hadsell, and Yann LeCun · 2005
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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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Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval
Bor-Chun Chen, Chu-Song Chen, and Winston H. Hsu · 2014
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Face Recognition Vendor Test (FRVT) Performance of Face Identification Algorithms NIST IR 8009
Patrick Grother and Mei Ngan · 2014
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Deep Learning Face Representation by Joint Identification-Verification
Y. Sun, Y. Chen, X. Wang, and X. Tang · 2014
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Deep Learning Face Representation from Predicting 10,000 Classes
Y. Sun, X. Wang, and X. Tang · 2014
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Learning face representation from scratch
Dong Yi, Zhen Lei, Shengcai Liao, and S. Li · 2014
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The Impact of Drug Policies on Children and Young People
Damon Barrett · 2015
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Pushing the frontiers of unconstrained face detection and recognition: Iarpa janus benchmark a
Brendan Klare, Benjamin Klein, Emma Taborsky, Austin Blanton, Jordan Cheney, Kristen C. Allen, Patrick Grother, Alan Mah, Mark Burge, and Anil K. Jain · 2015
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A review of face recognition against longitudinal child faces
Karl Ricanek, Shivani Bhardwaj, and Michael Sodomsky · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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FaceNet: A unified embedding for face recognition and clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
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Deeply learned face representations are sparse, selective, and robust
Y. Sun, X. Wang, and X. Tang · 2015
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Automatic face recognition of newborns, infants, and toddlers: A longitudinal evaluation
Lacey Best-Rowden, Yovahn Hoole, and Anil Jain · 2016
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Canada’s Missing – 2015 Fast Fact Sheet – MC/PUR Missing child subjects by province, sex and probable cause
”GOVERNMENT OF CANADA” · 2016
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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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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Overview of research on facial ageing using the fg-net ageing database
Gabriel Panis, Andreas Lanitis, Nicolas Tsapatsoulis, and Tim Cootes · 2016
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Frontal to profile face verification in the wild
S. Sengupta, J.C. Cheng, C.D. Castillo, V.M. Patel, R. Chellappa, and D.W. Jacobs · 2016
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A Discriminative Feature Learning Approach for Deep Face Recognition
Yandong Wen, Kaipeng Zhang, Zhifeng Li, and Yu Qiao · 2016
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Beat: An open-science web platform
A. Anjos, L. El-Shafey, and S. Marcel · 2017
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Growth and maturation
Neil Armstrong, Willem van Mechelen, and Adam DG Baxter-Jones · 2017
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Racial faces in the wild: Reducing racial bias by information maximization adaptation network
Mei Wang, Weihong Deng, Jiani Hu, Xunqiang Tao, and Yaohai Huang · 2019
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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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Towards Universal Representation Learning for Deep Face Recognition
Yichun Shi, Xiang Yu, Kihyuk Sohn, Manmohan Chandraker, and Anil Jain · 2020
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An Equalized Margin Loss for Face Recognition
J. Sun, W. Yang, J. Xue, and Q. Liao · 2020
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Parents reunite with son kidnapped 30 years ago, thanks to facial recognition technology. Global News, May 2020
Meaghan Wray · 2020
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SphereFace: Deep Hypersphere Embedding for Face Recognition
W. Liu, Y. Wen, Z. Yu, M. Li, B. Raj, and L. Song · 2017
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Agedb: the first manually collected, in-the-wild age database
Stylianos Moschoglou, Athanasios Papaioannou, Christos Sagonas, Jiankang Deng, Irene Kotsia, and Stefanos Zafeiriou · 2017
Cited alongside, same era.
Iarpa janus benchmark-b face dataset
Cameron Whitelam, Emma Taborsky, Austin Blanton, Brianna Maze, Jocelyn C. Adams, Tim Miller, Nathan D. Kalka, Anil K. Jain, James A. Duncan, Kristen E Allen, Jordan Cheney, and Patrick Grother · 2017
Cited alongside, same era.
Cross-age LFW: A database for studying cross-age face recognition in unconstrained environments
Tianyue Zheng, Weihong Deng, and Jiani Hu · 2017
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Celeb-500k: A large training dataset for face recognition
Jiajiong Cao, Yingming Li, and Zhongfei Zhang · 2018
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Vggface2: A dataset for recognising faces across pose and age
Q. Cao, L. Shen, W. Xie, O. M. Parkhi, and A. Zisserman · 2018
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D. Zeng, H. Shi, H. Du, J. Wang, Z. Lei, and T. Mei · 2020
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NCIC Active/Expired Missing and Unidentified Analysis Reports
”FEDERAL BUREAU OF INVESTIGATION” · 2021
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One label, one billion faces: Usage and consistency of racial categories in computer vision
Zaid Khan and Yun Fu · 2021
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Cross-quality lfw: A database for analyzing cross- resolution image face recognition in unconstrained environments
M. Knoche, S. Hormann, and G. Rigoll · 2021
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Is it easy to recognize baby’s age and gender?
Yang Liu, Ruili He, Xiaoqian Lv, Wei Wang, Xin Sun, and Shengping Zhang · 2021
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MagFace: A universal representation for face recognition and quality assessment
Qiang Meng, Shichao Zhao, Zhida Huang, and Feng Zhou · 2021
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QualFace: Adapting Deep Learning Face Recognition for ID and Travel Documents with Quality Assessment
João Tremoço, Iurii Medvedev, and Nuno Gonçalves · 2021
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UK Missing Persons Bureau – Missing Persons Data Report 2014/2015 15
”NATIONAL CRIME AGENCY” · 2022
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Face recognition in children: A longitudinal study
Keivan Bahmani and Stephanie Schuckers · 2022
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Live facial recognition is tracking kids suspected of being criminals. MIT Technology Review., October 2020
Karen Hao · 2022
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Double-blinded finder: A two-side secure children face recognition system
Xin Jin, Jicheng Lei, Shiming Ge, Chenggen Song, Haoyang Yu, and Chuanqiang Wu · 2022
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Adaface: Quality adaptive margin for face recognition
Minchul Kim, Anil K. Jain, and Xiaoming Liu · 2022
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Towards understanding the character of quality sampling in deep learning face recognition
Iurii Medvedev, João Tremoço, Beatriz Mano, Luís Espírito Santo, and Nuno Gonçalves · 2022
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