OCFR 2022: Competition on Occluded Face Recognition from Synthetically Generated Structure-Aware Occlusions

Pedro C. Neto, Fadi Boutros, Joao Ribeiro Pinto, Naser Damer, Ana F. Sequeira, Jaime S. Cardoso, Messaoud Bengherabi, Abderaouf Bousnat, Sana Boucheta, Nesrine Hebbadj, Mustafa Ekrem Erakin, Ugur Demir, Hazim Kemal Ekenel, Pedro Beber De Queiroz Vidal, David Menotti

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

4 Citations (Scopus)

Abstract

This work summarizes the IJCB Occluded Face Recognition Competition 2022 (IJCB-OCFR-2022) embraced by the 2022 International Joint Conference on Biometrics (IJCB 2022). OCFR-2022 attracted a total of 3 participating teams, from academia. Eventually, six valid submissions were submitted and then evaluated by the organizers. The competition was held to address the challenge of face recognition in the presence of severe face occlusions. The participants were free to use any training data and the testing data was built by the organisers by synthetically occluding parts of the face images using a well-known dataset. The submitted solutions presented innovations and performed very competitively with the considered baseline. A major output of this competition is a challenging, realistic, and diverse, and publicly available occluded face recognition benchmark with well defined evaluation protocols.

Original languageEnglish
Title of host publication2022 IEEE International Joint Conference on Biometrics, IJCB 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665463942
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Joint Conference on Biometrics, IJCB 2022 - Abu Dhabi, United Arab Emirates
Duration: 10 Oct 202213 Oct 2022

Publication series

Name2022 IEEE International Joint Conference on Biometrics, IJCB 2022

Conference

Conference2022 IEEE International Joint Conference on Biometrics, IJCB 2022
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period10/10/2213/10/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Funding

This work was financed by National Funds through the Portuguese funding agency, FCT - Fundac¸ão para a Ciência e a Tecnologia within project LA/P/0063/2020, and within the PhD grants “2021.06872.BD” and “SFRH/BD/137720/2018”. This research work has been also partially funded by the German Federal Ministry of Education and Research and the Hessen State Ministry for Higher Education, Research and the Arts within their joint support of the National Research Center for Applied Cybersecurity ATHENE.

FundersFunder number
National Research Center for Applied Cybersecurity ATHENE
Fundação para a Ciência e a TecnologiaSFRH/BD/137720/2018, LA/P/0063/2020
Bundesministerium für Bildung und Forschung
Hessisches Ministerium für Wissenschaft und Kunst

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