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
More filters
Journal Article
“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告
Journal ArticleDOI
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.
Journal ArticleDOI
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
More filters
Proceedings ArticleDOI
Disguised Faces in the Wild
TL;DR: A novel Disguised Faces in the Wild (DFW) dataset, consisting of over 11,000 images for understanding and pushing the current state-of-the-art for disguised face recognition, along with the phase-I results of the CVPR2018 competition.
Proceedings ArticleDOI
Deep 3D face identification
TL;DR: In this paper, a 3D face recognition algorithm using a deep convolutional neural network (DCNN) and a three-dimensional face expression augmentation technique was proposed. But, the authors only used a small number of 3D facial scans.
Proceedings ArticleDOI
Learning Non-linear Reconstruction Models for Image Set Classification
TL;DR: The proposed framework is extensively evaluated for the task of image set classification based face recognition on Honda/UCSD, CMU Mobo, YouTube Celebrities and a Kinect dataset and shows that the proposed method consistently achieves the best performance on all these datasets.
Proceedings ArticleDOI
Face Generation for Low-Shot Learning Using Generative Adversarial Networks
TL;DR: A generator from the Generative Adversarial Network is adapted to increase the size of training dataset to improve the accuracy and robustness of face recognition and it is concluded that the proposed algorithm for generating faces is effective in improving the identification accuracy and coverage.
Journal ArticleDOI
Joint and collaborative representation with local adaptive convolution feature for face recognition with single sample per person
TL;DR: By densely sampling and sparsely detecting facial points, JCR-ACF is extracted and robust local regions are learned and convolution features adaptive to the local regions and discriminative to the face identity are learned by using convolutional neural networks (CNN).