Trustable faces: Face data integrity against digital and physical attacks (TrustFace)

Trustable faces: Face data integrity against digital and physical attacks (TrustFace)

Project description

Face analysis has been used widely in many applications, like in mobile payment, online banking. However, face data can be vulnerable to digital and physical attacks. In this research, we attempt to explore the new generation of various face forgery, adversarial and presentation attacks, improve face data integrity, develop robust and reliable learning based face analysis approaches, establish resource efficient and explainable learning methods against general attacks for trustable face analysis. This research is expected to have a significant impact in the practical and social aspects due to the wide applicability of autonomous systems to our daily life.? This research includes both theoretical analysis and experimental validations using publicly available datasets with heterogeneous and fragmented data. Prototype systems will be developed with the collaboration of industry.?? The research is carried out in the Center for Machine Vision and Signal Analysis, University of Oulu.?
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Starting year

2022

End year

2024

Granted funding

Guoying Zhao Orcid -palvelun logo
457 658 €

Funder

Academy of Finland

Funding instrument

Targeted Academy projects

Call

ICT 2023: Frontier AI Technologies 2021

Other information

Funding decision number

345948

Fields of science

Computer and information sciences

Research fields

Tietojenkäsittelytieteet

Identified topics

consumer, customer