Makeup Detection Dataset
A dataset of photos of people with and without makeup for cosmetics recognition
DATASET
Computer Vision
Ability of a machine to interpret, analyze, and understand visual data
Re-identification
Recognition of the same object in different observations.
AR
Machine learning in augmented reality applications.
Classification
Process of recognition and grouping of objects into preset categories
2 000
with makeup and real photos without makeup.
3 weeks
project duration
Case Description
Collection of photos of people with makeup and real photos without makeup through crowdsourcing. One type of cosmetics per person: lipstick, eyeliner, eyeshadow
Facial classification based on makeup type, tagged in CVAT (Computer Vision Annotation Tool). Semantic segmentation of the face for detailed cosmetics recognition. Image matting for AR solutions
The dataset consists of two folders:
APPLICATION AREAS OF THE DATASET
Makeup Individualization:
Facial classification and cosmetics segmentation for personalized cosmetic recommendations based on a person's appearance
/01
Makeup Detection:
Classification of selfies with makeup to determine the presence of makeup in photos.
/03
Cosmetic Industry:
AR in Advertising:
Crowdsourced research for evaluating new cosmetic products.
Semantic segmentation and image matting for selfies to create advertising masks that demonstrate the effects of cosmetics in real time
/04
/02

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LLM Teamleads
Team
Arthur Kazukevich
Python-developer
Wadim Starosotnikow
Sergey Razumny
Senior quality control manager
TeamLead Crowd Solutions
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Enhanced Data Accuracy
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Non-disclosure agreement
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Multiple data storage options
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