Face Parsing Dataset

Project Overview:


Face Parsing Dataset: Our goal was to create a dataset that meticulously dissects human facial features, including eyes, nose, mouth, and skin. This precision-focused dataset aids significantly in enhancing the accuracy of facial recognition software and the realism of augmented reality applications.


We embarked on an extensive data collection journey, gathering a wide range of human facial images and providing detailed annotations for each facial feature.

Face Parsing Dataset
Face Parsing Dataset
Face Parsing Dataset
Face Parsing Dataset


  • Public datasets of human portraits.
  • Selfies and profile pictures from social media, were obtained with explicit permission.
  • Our studio captures, featuring diverse lighting, angles, and expressions.
  • CCTV footage, used in full compliance with legal requirements.
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Face Parsing Dataset
Face Parsing Dataset

Data Collection Metrics

  • Total Data Points: 200,000 facial images
  • Studio Captures: 50,000
  • Social Media Extracts: 80,000
  • Public Datasets: 50,000
  • CCTV Footage: 20,000

Annotation Process


  1. Face Detection: Our algorithms proficiently identified and outlined faces in images.
  2. Feature Segmentation: We split faces into segments like eyes, nose, mouth, eyebrows, ears, and hair.
  3. Sub-segmentation: For detailed analysis, parts of the eye, for example, were divided further.
  4. Attribute Annotation: Each facial feature was classified based on specific attributes.

Annotation Metrics

  • Total Annotations: 1,600,000
  • Faces Detected: 200,000
  • Feature Segmentations: 1,200,000 (approx. 6 per face)
  • Sub-segmentations: 100,000 (selected features)
  • Attribute Annotations: 100,000
Face Parsing Dataset
Face Parsing Dataset
Face Parsing Dataset
Face Parsing Dataset

Quality Assurance


Expert Review: A panel of dermatologists and makeup artists evaluated a portion of the annotations.
Automated Consistency Checks: Our algorithms diligently identified annotation inconsistencies.
Inter-annotator Agreement: Ensuring consistent tagging by overlapping data subsets among annotators.

QA Metrics

  • Annotations Reviewed by Experts: 160,000
  • Inconsistencies Identified and Corrected: 8,000


The Face Parsing Dataset project successfully curated a comprehensive database ideal for training and testing advanced facial recognition and augmented reality systems. Rigorous standards for collection and annotation ensured that the dataset stands as a premium resource for innovators in technology and research fields.


Quality Data Creation


Guaranteed TAT


ISO 9001:2015, ISO/IEC 27001:2013 Certified


HIPAA Compliance


GDPR Compliance


Compliance and Security

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