Face recognition using total loss function on face database with ID photos

With the development of deep neural networks, researchers have developed lots of algorithms related to face and achieved comparable results to human-level performance on several databases. However, few feature extraction models work well in the real world when the subject which is to be recognized h...

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التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Cui, Dongshun, Zhang, Guanghao, Hu, Kai, Han, Wei, Huang, Guang-Bin
مؤلفون آخرون: Interdisciplinary Graduate School (IGS)
التنسيق: مقال
اللغة:English
منشور في: 2021
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/151322
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المؤسسة: Nanyang Technological University
اللغة: English
id sg-ntu-dr.10356-151322
record_format dspace
spelling sg-ntu-dr.10356-1513222021-06-22T04:35:51Z Face recognition using total loss function on face database with ID photos Cui, Dongshun Zhang, Guanghao Hu, Kai Han, Wei Huang, Guang-Bin Interdisciplinary Graduate School (IGS) School of Electrical and Electronic Engineering Energy Research Institute @ NTU (ERI@N) Engineering::Electrical and electronic engineering Face Recognition Face Recognition Benchmark With the development of deep neural networks, researchers have developed lots of algorithms related to face and achieved comparable results to human-level performance on several databases. However, few feature extraction models work well in the real world when the subject which is to be recognized has limited samples, for example, only one ID photo can be obtained before the face recognition task. To our best knowledge, there is no face database which contains ID photos and pictures from the real world for a subject simultaneously. To fill this gap, we collected 100 celebrities’ ID photos and their about 1000 stills or life pictures and formed a face database called FDID. Besides, we proposed a novel face recognition algorithm and evaluated it with this new database on the real-life videos. 2021-06-22T04:35:50Z 2021-06-22T04:35:50Z 2019 Journal Article Cui, D., Zhang, G., Hu, K., Han, W. & Huang, G. (2019). Face recognition using total loss function on face database with ID photos. Optics and Laser Technology, 110, 227-233. https://dx.doi.org/10.1016/j.optlastec.2017.10.016 0030-3992 0000-0002-9703-0120 https://hdl.handle.net/10356/151322 10.1016/j.optlastec.2017.10.016 2-s2.0-85032988939 110 227 233 en Optics and Laser Technology © 2017 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Face Recognition
Face Recognition Benchmark
spellingShingle Engineering::Electrical and electronic engineering
Face Recognition
Face Recognition Benchmark
Cui, Dongshun
Zhang, Guanghao
Hu, Kai
Han, Wei
Huang, Guang-Bin
Face recognition using total loss function on face database with ID photos
description With the development of deep neural networks, researchers have developed lots of algorithms related to face and achieved comparable results to human-level performance on several databases. However, few feature extraction models work well in the real world when the subject which is to be recognized has limited samples, for example, only one ID photo can be obtained before the face recognition task. To our best knowledge, there is no face database which contains ID photos and pictures from the real world for a subject simultaneously. To fill this gap, we collected 100 celebrities’ ID photos and their about 1000 stills or life pictures and formed a face database called FDID. Besides, we proposed a novel face recognition algorithm and evaluated it with this new database on the real-life videos.
author2 Interdisciplinary Graduate School (IGS)
author_facet Interdisciplinary Graduate School (IGS)
Cui, Dongshun
Zhang, Guanghao
Hu, Kai
Han, Wei
Huang, Guang-Bin
format Article
author Cui, Dongshun
Zhang, Guanghao
Hu, Kai
Han, Wei
Huang, Guang-Bin
author_sort Cui, Dongshun
title Face recognition using total loss function on face database with ID photos
title_short Face recognition using total loss function on face database with ID photos
title_full Face recognition using total loss function on face database with ID photos
title_fullStr Face recognition using total loss function on face database with ID photos
title_full_unstemmed Face recognition using total loss function on face database with ID photos
title_sort face recognition using total loss function on face database with id photos
publishDate 2021
url https://hdl.handle.net/10356/151322
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