Thermal-to-Visible Face Synthesis and Recognition

Face is one of the most widely used biometrics. One key advantage of using faces as a biometric is that they do not require the cooperation of the test subject. Various face recognition (FR) systems have been developed over the last two decades. Recent advances in machine learning and computer vision methods have provided robust systems that achieve significant gains in performance of face recognition systems [5, 19]. Deep learning methods, enabled by the vast improvements in processing hardware coupled with the ubiquity of face data and algorithmic development, have led to significant improvements in face recognition accuracy, particularly in unconstrained scenarios [4, 5, 19, 20, 27]. Also, largely driven by social network companies, progress in face recognition research, development, and deployment have focused on faces collected in visible regimes of the electromagnetic spectrum.