mahostar/EasyShield_v2.5
EasyShield Anti Spoofing AI Model for edge devices (State-of-the-art) performance (Open Source) Deep Learning Model
This project helps secure face-based authentication systems against spoofing attacks like photos or video replays. It takes live video feeds or image sets as input and determines if the face presented is 'Real' or 'Fake' in real-time. Security managers, system integrators, and product managers developing or deploying facial recognition solutions for access control, KYC, or fraud prevention would use this.
No commits in the last 6 months.
Use this if you need to quickly integrate a high-accuracy, lightweight face anti-spoofing solution into an existing facial recognition system, especially on edge devices.
Not ideal if your primary concern is extremely low inference latency (under 10ms) and you are willing to compromise significantly on detection accuracy.
Stars
58
Forks
14
Language
Python
License
MIT
Category
Last pushed
Jun 18, 2025
Commits (30d)
0
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