Online web demo at https://www.doubango.org/webapps/face-liveness/
Full documentation for the SDK at https://www.doubango.org/SDKs/face-liveness/docs/
Supported languages (API): C++, C#, Java and Python
Open source Computer Vision Library: https://github.com/DoubangoTelecom/compv
To our knowledge we're the only company in the world that can perform 3D liveness check and identity concealment detection from a single 2D image. We outperform the competition (FaceTEC, BioID, Onfido, Huawei...) in speed and accuracy. Our implementation is Passive/Frictionless and only takes few milliseconds.
Identity concealment detects when a user tries to partially hide his/her face (e.g. 3D realistic mask, dark glasses...) or alter the facial features (e.g. heavy makeup, fake nose, fake beard...) to impersonate another user.
A facial recognition system without liveness detector is just useless.
We can detect and block all known spoofing attacks:
Paper Print, Screen, Video Replay, 3D (silicone, paper, tissue...) realistic face mask, 2D paper mask, Concealment...
|3D Liveness detection||Deepfake detection|
Our passive (frictionless) face liveness detector uses SOTA (State Of The Art) deep learning techniques and can be freely tested with your own images at https://www.doubango.org/webapps/face-liveness/
This version supports both Windows and Linux x86_64.
Checking out the source code
git clone --recurse-submodules -j8 https://github.com/DoubangoTelecom/FaceLivenessDetection-SDK
If you already have the code and want to update to the latest version:
git pull --recurse-submodules
Trying samples (C++, C#, Java and Python)
Go to the samples folder and choose your prefered language.