Special Issue on Face Presentation Attack Detection

Jun Wan, Sergio Escalera, Hugo Jair Escalante, Guodong Guo, Stan Z. Li

Research output: Contribution to journalEditorialpeer-review

4 Citations (Scopus)

Abstract

Face presentation attack detection, also termed Face Anti-Spoofing (FAS) [item 1), 2) in the Appendix), is a hot and challenging research topic that has received much attention from the computer vision and pattern recognition communities in the past. Owing to the development of deep learning and big data, recent advances in this and related fields has increased considerably. However, there are still several challenging tasks that deserve attention from the community, for instance robust techniques to unknown spoofing attacks, cross-domain generalization, and multi-modal fusion in images and video sequences. We edited this special issue with the goal of compiling the latest progress in the field and identifying promising research opportunities on FAS.

Original languageEnglish
Article number9467256
JournalIEEE Transactions on Biometrics, Behavior, and Identity Science
Volume3
Issue number3
Pages (from-to)282-284
Number of pages3
ISSN2637-6407
DOIs
Publication statusPublished - Jul 2021

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

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