Production-Grade Face Recognition Training Datasets
- Millions of face images balanced by ethnicity, age, and skin tone
- 68+ facial landmark keypoints per image — CV specialist annotation
- Covers security, biometrics, DMS/automotive, retail analytics & healthcare AI
- Multi-condition capture: poses, lighting, occlusions (masks, glasses, hats)
- GDPR-compliant, consent-verified, full IP licensing & audit trail
Talk to a Face Recognition Data Expert
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The Face Data Infrastructure Behind Leading Vision AI
Shaip delivers the facial recognition datasets that make models detect, identify, and understand human faces accurately in real-world conditions.
Precise, Diverse, Consent-Verified Face Recognition Training Data
Ready-to-license catalog of millions of annotated facial images with purpose-built custom collection across 50+ countries — delivering the demographic diversity and label accuracy that production AI demands.
Demographically Balanced by Design
Demographic quotas for ethnicity, Fitzpatrick skin tone, gender, and age group are enforced in every collection project from recruitment day one — not added as an afterthought.
Expert Facial Landmark Annotation
68+ keypoints per face — eye corners, nose tip, lip boundaries, jawline — annotated by CV specialists with multi-stage QA. 98%+ IAA verified across every project batch.
Real-World Capture Conditions
Multiple poses, expressions, lighting, occlusions (glasses, masks, hats), indoor/outdoor environments — matching your model's actual deployment scenario from day one.
Consent-First Legal Framework
Every subject provides explicit informed consent. Full data use agreements, licensing docs, consent records, and GDPR audit trail included — zero legal ambiguity for your compliance team.
Facial Recognition Dataset Types for Every AI Use Case
Browse ready-to-license off-the-shelf datasets — or commission a fully custom collection built to your demographic requirements, capture conditions, and annotation schema.
Face Detection & Localization
Bounding box annotations across every face — covering multiple faces per image, extreme sizes, partial occlusions, and crowded real-world scenes.
Facial Landmark (68+ Points)
Keypoints across eyes, nose, mouth, jaw, and brow contours — expert-validated placement for alignment, 3D reconstruction, and expression analysis.
Facial Expression & Emotion
Faces labeled with 7 discrete emotions and FACS action units — across diverse demographics and real-world conditions for nuanced expression recognition.
Multi-Condition Face Datasets
Controlled variation across pose (frontal, 3/4, profile), illumination (studio, low-light, outdoor), and camera distances — providing the distribution diversity.
Occluded Face Datasets
Faces with masks, sunglasses, hats, scarves, and partial occlusions — critical for liveness detection and surveillance AI operating in real public environments.
Demographically Diverse Faces
Explicitly balanced by ethnicity, skin tone, age group (infant to elderly), gender, and geographic origin — built to train global face recognition models.
In-Cabin Driver Monitoring (DMS)
Vehicle interior captures with IR/NIR lighting, overhead camera angles, and varying head poses — built for driver monitoring and ADAS model training.
Retail & Overhead Camera Faces
Top-down and wide-angle face images for retail surveillance and building access — with age, gender, and emotion annotations for customer analytics.
Biometric & Anti-Spoofing Datasets
Real vs. spoofed face pairs — photo attacks, screen replay, 3D masks, deepfake artifacts — for training liveness detection in biometric authentication.
Don't Just License Data — Build What Your Model Needs
Shaip operates at both ends of the face data pipeline: collecting raw images at scale and transforming them into richly labeled, model-ready datasets through expert annotation. One partner. Zero handoffs.
Controlled Studio Capture
Precise lighting, background, and pose control — ideal for biometric enrollment, face ID training, and building demographically balanced identity databases.
In-the-Wild / Natural Environment
Real-world face captures in uncontrolled conditions — outdoor scenes, varying light, crowds, and natural backgrounds for models that need production robustness.
Domain-Specific Capture (DMS, Retail, Clinical)
In-vehicle IR/NIR capture, overhead retail camera setups, and clinical lighting — custom protocols designed for your specific deployment environment and hardware.
Facial Landmark Annotation (68+ Points)
Per-face keypoint placement across eyes, nose, mouth, jaw, and brow — with expert-validated accuracy for 3D reconstruction, alignment, and expression analysis.
Emotion, Expression & Attribute Labeling
7 discrete emotions, FACS action units, age estimation, gender, skin tone, facial hair, occlusion type — multi-label annotation capturing the full semantic richness of face images.
Segmentation, Bounding Boxes & Diarization
Pixel-perfect face segmentation, tight bounding boxes, multi-person scene diarization, and depth estimation labels — for detection, tracking, and 3D face reconstruction models.
Face AI Use Cases Powered by Shaip Data
Every major facial recognition application needs domain-specific training data. Shaip delivers purpose-built datasets across all six verticals.
Security & Surveillance AI
Train face matching for CCTV, law enforcement, and access control — with diverse datasets that reduce false positives and meet regulatory requirements.
Face MatchingBiometric Authentication
Build face unlock and identity verification systems with liveness detection datasets covering real and spoofed attacks — across diverse demographics.
Liveness DetectionAutomotive Driver Monitoring
Train drowsiness and distraction monitoring with in-cabin IR face datasets captured in real vehicle conditions — balanced by driver demographics and lighting scenarios.
DMS / ADASRetail Face Analytics
Power customer analytics and emotion-based personalization with overhead face datasets labeled for demographics and emotional state — GDPR compliant.
Customer IntelligenceHealthcare & Medical AI
Enable patient identification, pain detection, and rare disease facial phenotyping with clinical datasets annotated with the precision required for medical AI.
Clinical Vision AIConsumer Devices & IoT
Train smartphone face unlock, smart home personalization, and IoT access with near-field face datasets across lighting conditions and device camera types.
Edge InferenceWhat Makes Shaip the World's Leading Face Data Partner
Not a scraping service. Not a generic crowdsourcing platform. Shaip is a purpose-built facial recognition data company with a decade of computer vision domain expertise.
10+ Years of CV Data Expertise
Since 2014, Shaip has built face datasets for the world's largest technology companies — with deep expertise in annotation schemas, capture protocols, and diversity requirements that production models demand.
Enforced Demographic Balancing
Demographic quotas by ethnicity, Fitzpatrick scale, age group, and gender are built into every collection project from day one — not aspirational targets added at delivery review.
Computer Vision Specialist Annotators
Our annotation teams are trained in facial anatomy and landmark placement — not general crowdworkers. Multi-stage QA with 98%+ IAA ensures your model trains on accurate, consistent labels.
Catalog + Custom — One Partner
Start with off-the-shelf face images to bootstrap your model. Commission custom collection for specific conditions. One vendor, one contract, one delivery process. Zero handoffs.
What Computer Vision Teams Say About Shaip
Shaip's dataset has been instrumental in enhancing our AI-driven anti-spoofing models. The diversity, quality, and structured metadata provided a strong foundation for improving fraud detection .
Shaip's diverse, ethically sourced datasets gave us the speed, quality, and compliance we needed. With ready-to-use data, we accelerated AI model training and significantly reduced systemic bias.
Shaip turned a complex Non-EU/UK facial dataset brief into a balanced, audit-ready corpus. Their age progression design and tiered QA gave our CV team clean, diverse data we could trust — without risk.
Anti-spoofing videos collected across 12,500 unique participants — balanced across 5 ethnicity groups with 12 metadata attributes, delivered in 4 phased batches at 720p or higher resolution
Facial images delivered across 7,000+ subjects — spanning multiple datasets covering emotion recognition, lighting variation, multi-angle poses, & 6 human expressions across diverse ethnicities
Non-EU/UK participants with time-separated photos — balanced 50/50 gender split and age bands covering South/Southeast Asia, Africa, Singapore & South America
Conversation to Annotated Face Dataset — 4 Steps
No vague timelines. No surprise scope changes. A direct, transparent path from your requirements to production-ready delivery.
Talk to a Vision Data Specialist
Submit the form. A Shaip CV data expert — not a generic SDR — responds within 1 business day to understand your model's exact requirements in depth.
Dataset Scoping & Proposal
We define demographic quotas, capture conditions, annotation schema, pose/expression/lighting requirements, volume, and format — then deliver a proposal with clear timeline and cost.
Pilot Batch & Quality Validation
A pilot batch lets your team validate annotation quality, demographic balance, and schema fit before full-scale production. Adjustments made before scale — not after.
Full Dataset Delivery & Scale
Delivered securely in PASCAL VOC, COCO JSON, or custom format — with full licensing documentation, consent records, and complete GDPR audit trail.
Your Face Recognition Model Is Only As Good As the Diversity in Its Training Data
Don’t let biased or poorly annotated face data limit your model’s real-world accuracy. Talk to a Shaip specialist and get a clear path to the diverse, consent-verified, expertly annotated facial recognition datasets.