Face++
Authenticate identities, reduce fraud, and create custom facial recognition applications with high accuracy.
What is Face++?
Face++ is a facial recognition platform that helps organisations verify identities and detect fraudulent activity. It provides APIs and SDKs for developers to build custom facial recognition features into their applications, without needing to develop the technology from scratch. The service uses machine learning models trained to identify and match faces with high accuracy across different lighting conditions, angles, and image qualities. Face++ is used by financial institutions, mobile app developers, and security services to authenticate users during account access, prevent identity fraud, and manage access control systems.
Key Features
Face detection and recognition
identifies faces in images and video streams with coordinates and confidence scores
Identity verification
compares two faces to confirm whether they belong to the same person
Liveness detection
distinguishes between real people and photographs or video replays to prevent spoofing attacks
Face attribute analysis
extracts details such as age, gender, expression, and head position from detected faces
Custom model training
allows organisations to train models on their own datasets for specific use cases
API and SDK integration
provides straightforward integration into web applications, mobile apps, and backend systems
Pros & Cons
Advantages
- High accuracy rates across diverse image qualities and face angles
- Free tier available for testing and small-scale projects before commitment
- Flexible API structure suitable for both simple integrations and complex custom applications
- Liveness detection helps reduce fraud from photograph-based attacks
Limitations
- Pricing details for paid tiers are not transparent on the public website; you need to contact sales for quotes
- Facial recognition raises privacy concerns; organisations must ensure compliance with local regulations like GDPR and obtain proper user consent
- Performance can vary depending on image quality, lighting, and face angle in real-world conditions
Use Cases
Banking and fintech: identity verification during account opening or high-value transactions
Mobile app security: enable apps or approve sensitive actions using face authentication
Access control: manage physical or digital access to restricted areas using facial recognition
Fraud prevention: detect and flag suspicious identity claims in insurance or lending applications
Age verification: estimate age for age-restricted services like alcohol or gambling platforms