Face recognition remains one of the most significant challenges within the field of biometrics. In spite of advances in machine learning, algorithms that can generalize to new settings and tolerate the myriad configurations that the human face can take when acquired by a sensor are elusive. The IJCB 2017 Face Recognition Challenge is designed to evaluate state-of-the-art face recognition systems with respect to cross-dataset generalization, open set face detection, and open set face recognition – all of whi
The competition consists of three distinct challenges. Participants are invited to compete on one or more of these.
Challenge 1: Since 1993 there has been a continuing sequence of challenges and evaluations in face recognition. At any given time, the face recognition community concentrates on one or two challenges. Success is measured by performance on the most popular evaluation at the time. Performance on past challenges is not considered or discussed, as a recent paper by one of our organizers points out . There are two innovations in this first challenge when compared to previous face recognition competitions. First,