Multimodal Face Anti-Spoofing Using Cross-Attention Between RGB, Depth, and Thermal Streams in Vision Transformers

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BABATUNDE, Surajudeen Adewumi; Omowunmi Adebajo; Adekunle Oni; Oluwaseye Adebajo; Godwin IGBINIGIE

Original Research (Published On: 02-Jun-2026 )

DOI : https://dx.doi.org/10.54364/cybersecurityjournal.2026.3127

BABATUNDE, Surajudeen Adewumi, Omowunmi Olabowale Adebajo, Adekunle Akeem Oni, Oluwaseye Adesina Adebajo and Godwin Omoghegbe-Aigbojie IGBINIGIE

J. Artif. Intell. Auton. Intell., 3 (1):466-484

BABATUNDE, Surajudeen Adewumi : Federal University of Agriculture, Abeokuta, Ogun State

Omowunmi Olabowale Adebajo : Department of Computer Engineering Bells University of Technology. Ota, Ogun State, Nigeria

Adekunle Akeem Oni : Department of Computer Engineering Bells University of Technology. Ota, Ogun State, Nigeria

Oluwaseye Adesina Adebajo : Anatomy Programme, College of Health Sciences Bowen University Iwo Campus Osun State, Nigeria

Godwin Omoghegbe-Aigbojie IGBINIGIE : Biomedical Engineering Department, Bells University of Technology. Ota, Ogun State, Nigeria

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DOI: https://dx.doi.org/10.54364/cybersecurityjournal.2026.3127

Article History: Received on: 24-Feb-26, Accepted on: 19-Apr-26, Published on: 02-Jun-26

Corresponding Author: BABATUNDE, Surajudeen Adewumi

Email: babatundesurajudeen@funaab.edu.ng

Citation: BABATUNDE, Surajudeen Adewumi (2026). Multimodal Face Anti-Spoofing Using Cross-Attention Between RGB, Depth, and Thermal Streams in Vision Transformers. J. Artif. Intell. Auton. Intell., 3 (1 ):466-484

Abstract

Facial recognition technology is increasingly being applied in highly secure settings; never-

theless, it remains vulnerable to more sophisticated forms of attacks such as printed images,

replayed videos, and three-dimensional face masks.

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Multimodal Face Anti-Spoofing Using Cross-Attention Between RGB, Depth, and Thermal Streams in Vision Transformers

Original Research (Published On: 02-Jun-2026 )

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