Abstract:
The following report discusses various facial recognition spoofing techniques in
use today, and compares various algorithms, that have been developed for
detecting the same. Continuing towards the previous semester’s goal of developing
a robust facial facial recognition system, an anti-spoofing module becomes a
necessity as it plays a very important role of differentiating between genuine face
and fake faces. Even the most advanced algorithms today, such as the FaceNet are
prone to spoofing attacks, like the warped photo attack, cut-photo attack etc.
Further, various deep-learning based architectures have been implemented and
their performance on the task of detecting spoofed images compared.
