Deep face recognition: A survey
Mei Wang,Weihong Deng +1 more
TLDR
A comprehensive review of the recent developments on deep face recognition can be found in this paper, covering broad topics on algorithm designs, databases, protocols, and application scenes, as well as the technical challenges and several promising directions.About:
This article is published in Neurocomputing.The article was published on 2021-03-14 and is currently open access. It has received 353 citations till now. The article focuses on the topics: Deep learning & Feature extraction.read more
Citations
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Journal Article
“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告
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A Survey of Deep Learning-Based Object Detection
TL;DR: This survey provides a comprehensive overview of a variety of object detection methods in a systematic manner, covering the one-stage and two-stage detectors, and lists the traditional and new applications.
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Deep neural network concepts for background subtraction:A systematic review and comparative evaluation
TL;DR: In this article, the authors provide a review of deep neural network concepts in background subtraction for novices and experts in order to analyze this success and to provide further directions.
MORPH: A Longitudinal Image Database of Normal Adult Age-Progression.
Karl Ricanek,Tamirat Tesafaye +1 more
TL;DR: It is concluded that the problem of age-progression on face recognition (FR) is not unique to the algorithm used in this work, and the efficacy of this algorithm is evaluated against the variables of gender and racial origin.
References
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Identifying facial phenotypes of genetic disorders using deep learning
Yaron Gurovich,Yair Hanani,Omri Bar,Guy Nadav,Nicole Fleischer,Dekel Gelbman,Lina Basel-Salmon,Peter Krawitz,Susanne B. Kamphausen,Martin Zenker,Lynne M. Bird,Karen W. Gripp +11 more
TL;DR: A facial image analysis framework, DeepGestalt, is presented, using computer vision and deep-learning algorithms, that quantifies similarities to hundreds of syndromes and potentially adds considerable value to phenotypic evaluations in clinical genetics, genetic testing, research and precision medicine.
Proceedings ArticleDOI
Graph embedding: a general framework for dimensionality reduction
TL;DR: A new supervised algorithm, Marginal Fisher Analysis (MFA), is proposed, for dimensionality reduction by designing two graphs that characterize the intra-class compactness and inter-class separability, respectively.
Proceedings ArticleDOI
Feature level fusion of hand and face biometrics
Arun Ross,Rohin Govindarajan +1 more
TL;DR: This work discusses fusion at the feature level in 3 different scenarios: (i) fusion of PCA and LDA coefficients of face; (ii) Fusion of LDA coefficient corresponding to the R,G,B channels of a face image; and (iii) fusionof face and hand modalities.
Journal ArticleDOI
Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition
Changxing Ding,Dacheng Tao +1 more
TL;DR: A Trunk-Branch Ensemble CNN model (TBE-CNN), which extracts complementary information from holistic face images and patches cropped around facial components, achieves state-of-the-art performance on three popular video face databases: PaSC, COX Face, and YouTube Faces.
Book ChapterDOI
Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval
TL;DR: A novel coding framework called Cross-Age Reference Coding (CARC), which is able to encode the low-level feature of a face image with an age-invariant reference space and can achieve state-of-the-art performance on both the dataset and other widely used dataset for face recognition across age, MORPH dataset.