Facets (new session)
Description
Metadata
Settings
owl:sameAs
Inference Rule:
b3s
b3sifp
dbprdf-label
facets
http://dbpedia.org/resource/inference/rules/dbpedia#
http://dbpedia.org/resource/inference/rules/opencyc#
http://dbpedia.org/resource/inference/rules/umbel#
http://dbpedia.org/resource/inference/rules/yago#
http://dbpedia.org/schema/property_rules#
http://www.ontologyportal.org/inference/rules/SUMO#
http://www.ontologyportal.org/inference/rules/WordNet#
http://www.w3.org/2002/07/owl#
ldp
oplweb
skos-trans
virtrdf-label
None
About:
Masked Face Recognition Dataset and Application
Goto
Sponge
NotDistinct
Permalink
An Entity of Type :
schema:ScholarlyArticle
, within Data Space :
covidontheweb.inria.fr
associated with source
document(s)
Type:
Academic Article
research paper
schema:ScholarlyArticle
New Facet based on Instances of this Class
Attributes
Values
type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
has title
Masked Face Recognition Dataset and Application
Creator
Wu, Hao
Hong, Qi
Miao, Yu
Chen, Heling
Huang, Baojin
Huang, Zhibing
Jiang, Kui
Liang, Jinbi
Pei, Yingjiao
Wang, Guangcheng
Wang, Nanxi
Wang, Zhongyuan
Xiong, Zhangyang
Yi, Peng
Source
ArXiv
abstract
In order to effectively prevent the spread of COVID-19 virus, almost everyone wears a mask during coronavirus epidemic. This almost makes conventional facial recognition technology ineffective in many cases, such as community access control, face access control, facial attendance, facial security checks at train stations, etc. Therefore, it is very urgent to improve the recognition performance of the existing face recognition technology on the masked faces. Most current advanced face recognition approaches are designed based on deep learning, which depend on a large number of face samples. However, at present, there are no publicly available masked face recognition datasets. To this end, this work proposes three types of masked face datasets, including Masked Face Detection Dataset (MFDD), Real-world Masked Face Recognition Dataset (RMFRD) and Simulated Masked Face Recognition Dataset (SMFRD). Among them, to the best of our knowledge, RMFRD is currently theworld's largest real-world masked face dataset. These datasets are freely available to industry and academia, based on which various applications on masked faces can be developed. The multi-granularity masked face recognition model we developed achieves 95% accuracy, exceeding the results reported by the industry. Our datasets are available at: https://github.com/X-zhangyang/Real-World-Masked-Face-Dataset.
has issue date
2020-03-20
(
xsd:dateTime
)
has license
arxiv
sha1sum (hex)
9e3a9bddd773cd34b186cbd3489a112598583294
resource representing a document's title
Masked Face Recognition Dataset and Application
resource representing a document's body
covid:9e3a9bddd773cd34b186cbd3489a112598583294#body_text
is
schema:about
of
named entity 'Therefore'
named entity 'current'
named entity 'academia'
named entity 'datasets'
named entity 'face'
named entity 'APPLICATIONS'
named entity 'KNOWLEDGE'
named entity 'WORLD'
named entity 'RECOGNITION'
named entity 'PERFORMANCE'
named entity 'MASKED'
named entity 'ACCESS'
named entity 'ADVANCED'
named entity 'EXCEEDING'
named entity 'BEST'
named entity 'EPIDEMIC'
named entity 'NUMBER OF'
named entity 'TECHNOLOGY'
named entity 'CASES'
named entity 'datasets'
named entity 'masked'
named entity 'Our'
named entity 'Face'
named entity 'applications'
named entity 'virus'
named entity 'datasets'
named entity 'industry'
named entity 'technology'
named entity 'advanced'
named entity 'conventional'
named entity 'industry'
named entity 'deep learning'
named entity 'face recognition'
named entity 'Face Recognition'
named entity 'Face Recognition'
named entity 'Recognition'
named entity 'face recognition'
named entity 'algorithm'
named entity 'face recognition'
named entity 'face recognition systems'
named entity 'face recognition'
named entity 'face recognition'
named entity 'face recognition'
named entity 'Tencent'
named entity 'facial recognition technology'
named entity 'video surveillance'
named entity 'face recognition'
named entity 'Dlib'
named entity 'training dataset'
named entity 'face recognition'
named entity 'face recognition'
named entity 'face recognition'
named entity 'infection'
named entity 'facial mask'
named entity 'face recognition'
named entity 'face recognition'
named entity 'access control'
named entity 'COVID-19'
named entity 'face recognition'
named entity 'face recognition'
named entity 'mobile payment'
named entity 'face recognition'
named entity 'COVID-19'
named entity 'face recognition'
named entity 'face recognition'
named entity 'COVID-19'
named entity 'face recognition'
named entity 'COVID-19'
named entity 'deep learning'
named entity 'face recognition'
named entity 'Baidu'
named entity 'algorithm'
named entity 'face recognition'
named entity 'facial feature'
◂◂ First
◂ Prev
Next ▸
Last ▸▸
Page 1 of 3
Go
Faceted Search & Find service v1.13.91 as of Mar 24 2020
Alternative Linked Data Documents:
Sponger
|
ODE
Content Formats:
RDF
ODATA
Microdata
About
OpenLink Virtuoso
version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software