Analysis of Generative Data Augmentation for Face Antispoofing

Jarred Orfao, Dustin van der Haar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


As technology advances, criminals continually find innovative ways to gain unauthorised access, increasing face spoofing challenges for face recognition systems. This demands the development of robust presentation attack detection methods. While traditional face antispoofing techniques relied on human-engineered features, they often lacked optimal representation capacity, creating a void that deep learning has begun to address in recent times. Nonetheless, these deep learning strategies still demand enhancement, particularly in uncontrolled environments. In this study, we employ generative models for data augmentation to boost the face antispoofing efficacy of a vision transformer. We also introduce an unsupervised keyframe selection process to yield superior candidate samples. Comprehensive benchmarks against recent models reveal that our augmentation methods significantly bolster the baseline performance on the CASIA-FASD dataset and deliver state-of-the-art results on the Spoof in the Wild database for protocols 2 and 3.

Original languageEnglish
Title of host publicationPattern Recognition Applications and Methods - 12th International Conference, ICPRAM 2023, Revised Selected Papers
EditorsMaria De Marsico, Gabriella Sanniti Di Baja, Ana Fred, Ana Fred
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages26
ISBN (Print)9783031547256
Publication statusPublished - 2024
Event12th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2023 - Lisbon, Portugal
Duration: 22 Feb 202324 Feb 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14547 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2023


  • Analysis
  • Face antispoofing
  • Generative data augmentation
  • Keyframe selection

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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