My Eyes Are Up Here: Promoting Focus on Uncovered Regions in Masked Face Recognition
dc.contributor.author | Neto, Pedro | |
dc.contributor.author | Boutros, Fadi | |
dc.contributor.author | Pinto, João Ribeiro | |
dc.contributor.author | Saffari, Mohsen | |
dc.contributor.author | Damer, Naser | |
dc.contributor.author | Sequeira, Ana F. | |
dc.contributor.author | Cardoso, Jaime S. | |
dc.contributor.editor | Brömme, Arslan | |
dc.contributor.editor | Busch, Christoph | |
dc.contributor.editor | Damer, Naser | |
dc.contributor.editor | Dantcheva, Antitza | |
dc.contributor.editor | Gomez-Barrero, Marta | |
dc.contributor.editor | Raja, Kiran | |
dc.contributor.editor | Rathgeb, Christian | |
dc.contributor.editor | Sequeira, Ana | |
dc.contributor.editor | Uhl, Andreas | |
dc.date.accessioned | 2021-10-04T08:43:49Z | |
dc.date.available | 2021-10-04T08:43:49Z | |
dc.date.issued | 2021 | |
dc.description.abstract | The recent Covid-19 pandemic and the fact that wearing masks in public is now mandatory in several countries, created challenges in the use of face recognition systems (FRS). In this work, we address the challenge of masked face recognition (MFR) and focus on evaluating the verification performance in FRS when verifying masked vs unmasked faces compared to verifying only unmasked faces. We propose a methodology that combines the traditional triplet loss and the mean squared error (MSE) intending to improve the robustness of an MFR system in the masked-unmasked comparison mode. The results obtained by our proposed method show improvements in a detailed step-wise ablation study. The conducted study showed significant performance gains induced by our proposed training paradigm and modified triplet loss on two evaluation databases. | en |
dc.identifier.isbn | 978-3-88579-709-8 | |
dc.identifier.pissn | 1617-5468 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/37465 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-315 | |
dc.subject | Face recognition | |
dc.subject | masked face recognition | |
dc.subject | Covid-19 | |
dc.subject | triplet loss | |
dc.subject | vggface2 | |
dc.title | My Eyes Are Up Here: Promoting Focus on Uncovered Regions in Masked Face Recognition | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 30 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 21 | |
gi.conference.date | 15.-17. September 2021 | |
gi.conference.location | International Digital Conference | |
gi.conference.sessiontitle | Regular Research Papers |
Dateien
Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
- Name:
- biosig2021_proceedings_03.pdf
- Größe:
- 235.76 KB
- Format:
- Adobe Portable Document Format