Recent Progress on Face Presentation Attack Detection of 3D Mask Attack

Si Qi Liu, Pong C. Yuen*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

With the development of 3D reconstruction and 3D printing technologies, customizing super-real 3D facial mask at an affordable cost becomes feasible, which brings a big challenge to face presentation attack detection (PAD). With the boosting of face recognition application in wide scenarios, there is an urgent need to solve the 3D facial mask attack problem. Since this appearance and material of 3D masks could vary in a much larger range compared with traditional 2D attacks, 2D face PAD solutions introduced in previous chapters may not work any longer. In order to attract more attention to 3D mask face PAD, this book chapter summarizes the progress in the past few years, as well as publicly available datasets. Finally, open problems and possible future directions are discussed.

Original languageEnglish
Title of host publicationHandbook of Biometric Anti-Spoofing
Subtitle of host publicationPresentation Attack Detection and Vulnerability Assessment
EditorsSébastien Marcel, Julian Fierrez, Nicholas Evans
Place of PublicationSingapore
PublisherSpringer
Pages231-259
Number of pages29
Edition3rd
ISBN (Electronic)9789811952883
ISBN (Print)9789811952876, 9789811952906
DOIs
Publication statusPublished - 23 Feb 2023

Publication series

NameAdvances in Computer Vision and Pattern Recognition
ISSN (Print)2191-6586
ISSN (Electronic)2191-6594

Scopus Subject Areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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