Domain Generalization with Pseudo-Domain Label for Face Anti-spoofing

Young Eun Kim, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Face anti-spoofing (FAS) plays an important role in protecting face recognition systems from face representation attacks. Many recent studies in FAS have approached this problem with domain generalization technique. Domain generalization aims to increase generalization performance to better detect various types of attacks and unseen attacks. However, previous studies in this area have defined each domain simply as an anti-spoofing datasets and focused on developing learning techniques. In this paper, we proposed a method that enables network to judge its domain by itself with the clustered convolutional feature statistics from intermediate layers of the network, without labeling domains as datasets. We obtained pseudo-domain labels by not only using the network extracting features, but also using depth estimators, which were previously used only as an auxiliary task in FAS. In our experiments, we trained with three datasets and evaluated the performance with the remaining one dataset to demonstrate the effectiveness of the proposed method by conducting a total of four sets of experiments.

Original languageEnglish
Title of host publicationPattern Recognition - 6th Asian Conference, ACPR 2021, Revised Selected Papers
EditorsChristian Wallraven, Qingshan Liu, Hajime Nagahara
PublisherSpringer Science and Business Media Deutschland GmbH
Pages431-442
Number of pages12
ISBN (Print)9783031023743
DOIs
Publication statusPublished - 2022
Event6th Asian Conference on Pattern Recognition, ACPR 2021 - Virtual, Online
Duration: 2021 Nov 92021 Nov 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13188 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th Asian Conference on Pattern Recognition, ACPR 2021
CityVirtual, Online
Period21/11/921/11/12

Keywords

  • Domain generalization
  • Face anti spoofing
  • Meta learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint

Dive into the research topics of 'Domain Generalization with Pseudo-Domain Label for Face Anti-spoofing'. Together they form a unique fingerprint.

Cite this