USE CASE
Makeup Before/After Image Collection
A dataset of photos of people with and without makeup for cosmetics recognition
Computer Vision
Ability of a machine to interpret, analyze, and understand visual data
AR
Machine learning in augmented reality applications
Re-identification
Recognition of the same object in different observations
Classification
Process of recognition and grouping of objects into preset categories
2 000
with makeup and real photos without makeup
3 weeks
project duration
Our Partners
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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
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APPLICATION AREAS OF THE DATASET
Makeup Individualization:
Facial classification and cosmetics segmentation for personalized cosmetic recommendations based on a person's appearance
AR in Advertising:
Semantic segmentation and image matting for selfies to create advertising masks that demonstrate the effects of cosmetics in real time
Makeup Detection:
Classification of selfies with makeup to determine the presence of makeup in photos
Cosmetic Industry:
Crowdsourced research for evaluating new cosmetic products
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Why
Training Data
- Quality Assurance:
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Enhanced Data Accuracy
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Consistency in Labels
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Reliable Ground Truth
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Mitigation of Annotation Biases
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Cost and Time Efficiency
- Data Security and Confidentiality:
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GDPR Compliance
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Non-disclosure agreement
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Data Encryption
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Multiple data storage options
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Access Controls and Authentication
- Expert Team:
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6 years in industry
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35 top project managers
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40+ languages
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100+ countries
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250k+ assessors
- Flexible and Scalable Solutions:
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24/7 availability of customer service
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100% post payment
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$550 minimum check
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Variable Workload
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Customized Solutions
Team leads project
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Sergey Razumny
TeamLead Crowd Solutions
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Arthur Kazukevich
Python-developer
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Wadim Starosotnikow
Senior quality control manager
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