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- Checking out the source code
- Trying samples (C++, C#, Java and Python)
- Getting help
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Online web demo at https://www.doubango.org/webapps/face-liveness/
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Full documentation for the SDK at https://www.doubango.org/SDKs/face-liveness/docs/
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Supported languages (API): C++, C#, Java and Python
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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...
The next video (https://youtu.be/4irfRCiOx1w) shows a stress test on our implementation using different type of attacks:
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.
The deep learning models are hosted on private repository for obvious reasons. You have to send us a mail with your company name and Github user name (to be added to the private repo). The mail must come from @YourCompanyName, mails from other domains (e.g. @Gmail) will be ignored. The terms of use do not allow you to decompile or reverse engineer the models.
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
Go to the samples folder and choose your prefered language.
Please check our discussion group or twitter account