Enhanced Face Authentication With Separate Loss Functions
This work addresses security and usability in mobile authentication, but appears incremental as it builds on existing architectures without demonstrating broad improvements.
The paper tackles face authentication for phone unlocking by proposing two new loss functions, LMCot and Double Loss, applied to face recognition and anti-spoofing, but does not report concrete performance numbers.
The overall objective of the main project is to propose and develop a system of facial authentication in unlocking phones or applications in phones using facial recognition. The system will include four separate architectures: face detection, face recognition, face spoofing, and classification of closed eyes. In which, we consider the problem of face recognition to be the most important, determining the true identity of the person standing in front of the screen with absolute accuracy is what facial recognition systems need to achieve. Along with the development of the face recognition problem, the problem of the anti-fake face is also gradually becoming popular and equally important. Our goal is to propose and develop two loss functions: LMCot and Double Loss. Then apply them to the face authentication process.