Crossing Domains for AU Coding: Perspectives, Approaches, and Measures.
Cross-domain generalizability
facial action unit detection
transfer learning
Journal
IEEE transactions on biometrics, behavior, and identity science
ISSN: 2637-6407
Titre abrégé: IEEE Trans Biom Behav Identity Sci
Pays: United States
ID NLM: 101764173
Informations de publication
Date de publication:
Apr 2020
Apr 2020
Historique:
entrez:
8
5
2020
pubmed:
8
5
2020
medline:
8
5
2020
Statut:
ppublish
Résumé
Facial action unit (AU) detectors have performed well when trained and tested within the same domain. How well do AU detectors transfer to domains in which they have not been trained? We review literature on cross-domain transfer and conduct experiments to address limitations of prior research. We evaluate generalizability in four publicly available databases. EB
Identifiants
pubmed: 32377637
doi: 10.1109/tbiom.2020.2977225
pmc: PMC7202467
mid: NIHMS1561930
doi:
Types de publication
Journal Article
Langues
eng
Pagination
158-171Subventions
Organisme : NIMH NIH HHS
ID : R01 MH096951
Pays : United States
Organisme : NINDS NIH HHS
ID : UH3 NS100549
Pays : United States
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