TY  - CHAP
AU  - Jun Wan
AU  - Guodong Guo
AU  - Sergio Escalera
AU  - Hugo Jair Escalante
AU  - Stan Z Li
PY  - 2023//
TI  - Face Anti-spoofing Progress Driven by Academic Challenges
T2  - SLCV
BT  - Advances in Face Presentation Attack Detection
SP  - 1–15
N2  - With the ubiquity of facial authentication systems and the prevalence of security cameras around the world, the impact that facial presentation attack techniques may have is huge. However, research progress in this field has been slowed by a number of factors, including the lack of appropriate and realistic datasets, ethical and privacy issues that prevent the recording and distribution of facial images, the little attention that the community has given to potential ethnic biases among others. This chapter provides an overview of contributions derived from the organization of academic challenges in the context of face anti-spoofing detection. Specifically, we discuss the limitations of benchmarks and summarize our efforts in trying to boost research by the community via the participation in academic challenges
UR  - https://link.springer.com/chapter/10.1007/978-3-031-32906-7_1
N1  - HUPBA
ID  - Jun Wan2023
ER  -