tencent cloud

Face Recognition

Product Introduction
Overview
Strengths
Use Cases
Purchase Guide
Billing Overview
Purchase Method
Payment Overdue
Operation Guide
Operation Process
API Documentation
History
Introduction
API Category
Making API Requests
Face Detection and Analysis APIs
Facial Feature Localization APIs
Face Comparison APIs
Group Management APIs
Face Search APIs
Face Verification APIs
Image-based Liveness Detection (High Precision) APIs
Data Types
Error Codes
FACEID Policy
Privacy Policy
Data Processing And Security Agreement
Service Level Agreement

Introduction

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Last updated: 2026-01-29 16:42:31

Accurate recognition

Face Recognition has industry-leading accuracy and is record-breaking in international competitions. It achieved 99.80% accuracy in LFW 2017 and ranked 1st in terms of first-attempt recognition rate (83.29%) in the MegaFace million-scale dataset.

High stability

Face Recognition was tested by Tencent products' massive user base and complex use cases and is proven to be highly reliable and robust with a 99.9% availability rate.

Leading algorithms

Based on the 3rd generation Tencent YouTu Grandmother Model, Face Recognition was optimized by various training methods such as metric learning, transfer learning, and multi-task learning. Its customized fine-tuning or distilling models can meet performance and latency requirements in different use cases.

Ease of use

Face Recognition offers multiple APIs and offline SDKs which enable fast applications and devices integration and satisfy cloud and device demands.

Diverse use cases

Face Recognition is used in a wide variety of use cases such as face recognition access control and attendance, event sign-in, face recognition payment, and face recognition login.

Real-time response

Face Recognition features high concurrence, high throughput, and low latency. It can search and process millions of faces in hundreds of milliseconds, meeting your needs in real time.

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