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Advances in Face Presentation Attack Detection
Jun Wan
Guodong Guo
Sergio Escalera
Hugo Jair Escalante
Stan Z. Li
出版
Springer Nature
, 2023-07-06
主題
Computers / Artificial Intelligence / Computer Vision & Pattern Recognition
Computers / Image Processing
Computers / Artificial Intelligence / General
Computers / Security / General
Computers / Software Development & Engineering / General
Computers / Optical Data Processing
Computers / Security / Network Security
ISBN
3031329066
9783031329067
URL
http://books.google.com.hk/books?id=DCrKEAAAQBAJ&hl=&source=gbs_api
EBook
SAMPLE
註釋
This book revises and expands upon the prior edition of
Multi-Modal Face Presentation Attack Detection
. The authors begin with fundamental and foundational information on face spoofing attack detection, explaining why the computer vision community has intensively studied it for the last decade. The authors also discuss the reasons that cause face anti-spoofing to be essential for preventing security breaches in face recognition systems. In addition, the book describes the factors that make it difficult to design effective methods of face presentation attack detection challenges. The book presents a thorough review and evaluation of current techniques and identifies those that have achieved the highest level of performance in a series of ChaLearn face anti-spoofing challenges at CVPR and ICCV. The authors also highlight directions for future research in face anti-spoofing that would lead to progress in the field. Additional analysis, new methodologies, and a more comprehensive survey of solutions are included in this new edition.