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Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition
[article]
2018
arXiv
pre-print
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As opposed to current techniques for age-invariant face recognition, which either directly extract age-invariant features for recognition, or first synthesize a face that matches target age before feature ...
Moreover, we propose a new large-scale Cross-Age Face Recognition (CAFR) benchmark dataset to facilitate existing efforts and push the frontiers of age-invariant face recognition research. ...
shapes and textures dramatically change over time, making learning age-invariant patterns difficult. 3) Current learning based cross-age face recognition models are limited by existing cross-age databases ...
arXiv:1809.00338v2
fatcat:qxg7d64n35fjzay2bdgcajlw4q
Look across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition
2019
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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To this end, we propose a deep Age-Invariant Model (AIM) for face recognition in the wild with three distinct novelties. ...
Third, we develop effective and novel training strategies for end-to-end learning the whole deep architecture, which generates powerful age-invariant face representations explicitly disentangled from the ...
Figure 1 : 1 Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition. ...
doi:10.1609/aaai.v33i01.33019251
fatcat:eaf5rdgns5edpnzfwzm7c72yde
Age Estimation Guided Convolutional Neural Network for Age-Invariant Face Recognition
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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The carefully designed CNN model can learn age-invariant features for face recognition. ...
While very promising results have been shown on face recognition related problems, age-invariant face recognition still remains a challenge. ...
In this paper, we propose an age estimation task guided face recognition framework to learn age-invariant features. ...
doi:10.1109/cvprw.2017.77
dblp:conf/cvpr/ZhengDH17
fatcat:5uehsilqefcfxjp4uic5uicjiu
An improved age invariant face recognition using data augmentation
2021
Bulletin of Electrical Engineering and Informatics
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Over the years, researchers have devised different techniques to improve the accuracy of age invariant face recognition (AIFR) systems. ...
stages, thus addressing the problem of few available training aging for face recognition dataset. ...
and retrieval system using coupled auto-encoder networks (CAN) Age invariant face recognition based on texture embedded discriminative graph model. ...
doi:10.11591/eei.v10i1.2356
fatcat:n2aaebf6cfdjtluyimmnv64pre
Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition
[article]
2018
arXiv
pre-print
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As facial appearance is subject to significant intra-class variations caused by the aging process over time, age-invariant face recognition (AIFR) remains a major challenge in face recognition community ...
To reduce the intra-class discrepancy caused by the aging, in this paper we propose a novel approach (namely, Orthogonal Embedding CNNs, or OE-CNNs) to learn the age-invariant deep face features. ...
As a major challenge in face recognition, age-invariant face recognition (AIFR) is extremely valuable on various application scenarios, such as looking for lost children after decades, matching face images ...
arXiv:1810.07599v1
fatcat:i27pjg24dbdyzhpm5kvuf2cc4i
Deep Architectures for Face Attributes
[article]
2016
arXiv
pre-print
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We train a deep convolutional neural network to perform identity classification using a new dataset of public figures annotated with age, gender, ethnicity and emotion labels, and then fine-tune it for ...
We find that prediction of age and emotion is improved by fine-tuning from earlier layers onward, presumably because deeper layers are progressively invariant to non-identity related changes in the input ...
Acknowledgments We would like to thank Neil O'Hare for collaborating with us on the search engine query logs, and the entire Yahoo Vision and Machine Learning Team. ...
arXiv:1609.09018v1
fatcat:mpuhb6cnebgl7c2jc46gnzf52e
Temporal Analysis Of Adaptive Face Recognition
2014
Journal of Artificial Intelligence and Soft Computing Research
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Experimental results on FGNET and MORPH aging database using commercial VeriLook face recognition engine demonstrate that continuous template updating is an effective and simple way to adapt to variations ...
Therefore, this paper first analyzes the performance of existing baseline facial representations, based on local features, under ageing effect then investigates the use of template update procedures for ...
the most robust face recognizer to be integrated with ageing invariant solutions for optimal performance. ...
doi:10.1515/jaiscr-2015-0012
fatcat:nxylmb622rahli5kudm3fkctyu
Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face Recognition
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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While considerable progresses have been made on face recognition, age-invariant face recognition (AIFR) still remains a major challenge in real world applications of face recognition systems. ...
In order to address this problem, we propose a novel deep face recognition framework to learn the ageinvariant deep face features through a carefully designed CNN model. ...
There are very limited work directly on age-invariant face recognition (AIFR), which aims to address the face matching problem in the presence of remarkable aging variations [26] . ...
doi:10.1109/cvpr.2016.529
dblp:conf/cvpr/WenL016
fatcat:vuuvzzxjzvddjosvagupyhcspe
Extreme Learning Machine-Based Age-Invariant Face Recognition With Deep Convolutional Descriptors
2022
International Journal of Applied Metaheuristic Computing
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from fully-connected layer of pre-trained AlexNet CNN model, in a context of age-invariant face recognition. ...
The principal intention of this paper is to study face recognition across age progression at two levels: feature extraction and classification. ...
AlexNet CNN model, in a context of age-invariant face recognition. ...
doi:10.4018/ijamc.290540
fatcat:5weiw4k7rjeonaaldt655g3wga
Age Gap Reducer-GAN for Recognizing Age-Separated Faces
[article]
2020
arXiv
pre-print
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Both visual fidelity and quantitative evaluations demonstrate the efficacy of the proposed architecture on different facial age databases for age-separated face recognition. ...
The key idea of this approach is to learn the age variations across time by conditioning the input image on the subject's gender and the target age group to which the face needs to be progressed. ...
[19] developed a 3D facial aging model to address the problem of age-invariant face recognition. ...
arXiv:2011.05897v1
fatcat:wp4runa63bashotjociwv7hl6m
Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition
[chapter]
2018
Lecture Notes in Computer Science
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As facial appearance is subject to significant intra-class variations caused by the aging process over time, age-invariant face recognition (AIFR) remains a major challenge in face recognition community ...
To reduce the intraclass discrepancy caused by the aging, in this paper we propose a novel approach (namely, Orthogonal Embedding CNNs, or OE-CNNs) to learn the age-invariant deep face features. ...
As a major challenge in face recognition, age-invariant face recognition (AIFR) is extremely valuable on various application scenarios, such as looking for lost children after decades, matching face images ...
doi:10.1007/978-3-030-01267-0_45
fatcat:rkjd3vg4ofhwfd6ljgbjfzg4nm
Jointly De-biasing Face Recognition and Demographic Attribute Estimation
[article]
2020
arXiv
pre-print
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We present a novel de-biasing adversarial network (DebFace) that learns to extract disentangled feature representations for both unbiased face recognition and demographics estimation. ...
The experimental results show that our approach is able to reduce bias in face recognition as well as demographics estimation while achieving state-of-the-art performance. ...
Cross-age Face Recognition We also conduct experiments on two cross-age face recognition datasets, i.e., FG-NET 2 and CACD-VS [2] , to evaluate the age-invariant identity features learned by DebFace. ...
arXiv:1911.08080v4
fatcat:2cavhrnfezggjh6jffhpxzhfoy
DAIL: Dataset-Aware and Invariant Learning for Face Recognition
[article]
2021
arXiv
pre-print
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To achieve good performance in face recognition, a large scale training dataset is usually required. ...
In this paper, we propose DAIL: Dataset-Aware and Invariant Learning to resolve the above-mentioned issues. ...
However, transfer learning based
[31]. ...
arXiv:2101.05419v1
fatcat:l7n4rr3r5ravrdlg5byhjho57u
Decorrelated Adversarial Learning for Age-Invariant Face Recognition
[article]
2019
arXiv
pre-print
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There has been an increasing research interest in age-invariant face recognition. ...
is useful for face recognition. ...
Importantly, this will improve robustness of x id for age-invariant face recognition. ...
arXiv:1904.04972v1
fatcat:4ugt6ltxffasxhppcwqv5uyo7y
Modeling of Facial Aging and Kinship: A Survey
[article]
2018
arXiv
pre-print
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2018 pre-print arXiv:1802.04636v1 fatcat:ulanapksg5dq5kedtt3xijo22a
for age progression, age estimation, age-invariant facial characterization, and kinship verification from visual data. ...
In particular, we provide an up-to date, complete list of available annotated datasets and an in-depth analysis of geometric, hand-crafted, and learned facial representations that are used for facial aging ...
AGE-INVARIANT FACIAL CHARACTERIZATION Age-invariant facial characterization involves two basic tasks: age-invariant face recognition and cross-age face verification. ...
arXiv:1802.04636v2
fatcat:hh3dl5j5gzdzfl7yap44ku3xxm
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