eKYC Face-Verification Pipeline

End-to-end face verification pairing RetinaFace detection, MiniFASNet liveness / anti-spoofing, and ArcFace recognition for high-security authentication.

Computer VisionRetinaFaceArcFaceMiniFASNetAnti-spoofFastAPI

The problem

Remote onboarding and authentication need to prove two things at once: this is a real, live person and this is the right person. A naive face-match is trivially defeated by a printed photo or a phone screen.

What I built

A complete eKYC pipeline that runs the full verification chain in one request:

  1. Detection — RetinaFace locates and aligns the face, even at awkward angles and lighting.
  2. Liveness / anti-spoofing — MiniFASNet rejects print, screen-replay, and mask attacks before any matching happens.
  3. Recognition — ArcFace produces a discriminative embedding and matches it against the reference identity.

Architecture

  • Models exported and optimised for low-latency inference.
  • A FastAPI service wraps the chain behind a clean verification endpoint that returns a decision plus per-stage confidence.
  • Designed so each stage is independently swappable and monitorable.

Outcome

A security-first verification flow where spoofing is caught early and recognition only runs on confirmed-live faces — suitable for onboarding, access control, and high-assurance login.

What you get

I can build or harden a face-verification / eKYC flow for your product, including liveness, the recognition backbone, and a deployable inference service.

Interested in this?

Let's build it for your team

I can adapt this solution to your use case — or build something new from scratch.