Introduction to Presentation Attack Detection in Face Biometrics and Recent Advances
원문 초록
The main scope of this chapter is to serve as an introduction to face presentation attack detection, including key resources and advances in the field in the last few years. The next pages present the different presentation attacks that a face recognition system can confront, in which an attacker presents to the sensor, mainly a camera, a Presentation Attack Instrument (PAI), that is generally a photograph, a video, or a mask, to try to impersonate a genuine user. First, we make an introduction of the current status of face recognition, its level of deployment, and its challenges. In addition, we present the vulnerabilities and the possible attacks that a face recognition system may be exposed to, showing that way the high importance of presentation attack detection methods. We review different types of presentation attack methods, from simpler to more complex ones, and in which cases they could be effective. Then, we summarize the most popular presentation attack detection methods to deal with these attacks. Finally, we introduce public datasets used by the research community for exploring vulnerabilities of face biometrics to presentation attacks and developing effective countermeasures against known PAIs.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection
VoxAtnNet: A 3D Point Clouds Convolutional Neural Network for Generalizable Face Presentation Attack Detection
Attributes Shape the Embedding Space of Face Recognition Models
Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space
DiffProb: Data Pruning for Face Recognition
StoryReasoning Dataset: Using Chain-of-Thought for Scene Understanding and Grounded Story Generation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.