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2,937 People with Occlusion and Multi-pose Face Recognition Data

Face recognition

Face occlusion

Multi-pose per person

Face with mask

Multiple light conditions

Multiplescenes

blockage

closure

stoppage

block

stop

obstruction

blocking

occluded

front

occlusive

check

closing

embolism

apoplexy

shutdown

hindrance

blockade

thrombosis

impaction

tampons

arrest

close

congestion

embolus

fastener

hitch

obturation

seal

stopper

abocclusion

blocks

clog

clot

clotting

constipation

holdup

impediment

occludent

plug

stoppages

stopples

stops

tampon

thrombus

airlock

barrier

cap

catch

clogging

cork

plugging

posture

perplex

puzzle

mystify

nonplus

bewilder

gravel

flummox

position

baffle

amaze

dumbfound

masquerade

beat

stick

stupefy

impersonate

attitude

place

stance

model

present

affectation

mannerism

attitudinize

sit

put

submit

show

airs

front

propose

suggest

pretense

propound

affectedness

raise

strike

a

pose

constitute

facade

personate

show

off

advance

pretend

act

bluff

arrange

put

on

airs

peacock

posing

confront

look

meet

front

facing

surface

encounter

side

brave

grimace

experience

visage

address

veneer

countenance

tackle

cover

oppose

confronting

defy

expression

aspect

appearance

cheek

watch

challenge

nerve

font

overlook

endure

withstand

suffer

brass

cope

with

dial

head

exterior

typeface

handle

undergo

be

facing

facade

face

up

facial

expression

physiognomy

beard

boldness

outside

deal

faces

2,937 People with Occlusion and Multi-pose Face Recognition Data, for each subject, 200 images were collected. The 200 images includes 4 kinds of light conditions * 10 kinds of occlusion cases (including non-occluded case) * 5 kinds of face pose. This data can be applied to computer vision tasks such as occluded face detection and recognition.rn

This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.

Specifications

Specifications

Data size

2,937 people, 200 images per person

Race distribution

Asian(Vietam .etc.)

Gender distribution

1,480 males , 1,457 females

Age distribution

ranging from teenager to the elderly, the middle-aged and young people are the majorities

Collecting environment

including indoor and outdoor scenes

Data diversity

multiple face poses, multiple occlusion cases, multiple ages, multiple light conditions and scenes

Device

cellphone

Data format

.jpg

Accuracy

the accuracy of labels of face pose, occlusion case, gender and age is more than 97%

Sample

Sample

Waiting For Data

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