Recent Advances on Cross-Domain Face Recognition

Abstract

Face recognition is a significant and pervasively applied computer vision task. With the specific application scenarios being explored gradually, general face recognition methods dealing with visible light images are unqualified. Cross-domain face recognition refers to a series of methods in response to face recognition problems whose inputs may come from multiple modalities, such as visible light images, sketch, near infrared images, 3D data, low-resolution images, thermal infrared images, or cross different ages, expressions, and ethnicities. Compared with general face recognition, cross-domain face recognition has not been widely explored and only few literatures systematically discuss this topic. Face recognition aiming at matching face images from photographs and other image modalities, which is usually called heterogeneous face recognition, has larger cross-domain gap and is a harder problem in this topic. This paper mainly investigates heterogeneous face databases, provides an up-to-date review of research efforts, and addresses common problems and related issues in cross-domain face recognition techniques.