Survey of Face Liveness Detection for Unsupervised Locations
Derek Apgar, Muhammad Rizwan Abid · 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) · 2021
Spoofing attacks represent a major threat to facial recognition systems. There are many types of attacks that can be carried out, ranging from 2D photo attacks to 3D mask attacks. Facial recognition systems must defend against such attacks using state-of-the-art anti-spoofing countermeasures. The current Covid-19 outbreak has increased the need for facial recognition, exacerbating the issue of secure facial recognition systems. This paper contains an overview of face liveness detection methods, mainly in the domain of deep learning, and how these methods combat the threat of non-live faces.