Rethinking Vision Transformer and Masked Autoencoder in Multimodal Face Anti-Spoofing

Recently, vision transformer (ViT) based multimodal learning methods have been proposed to improve the robustness of face anti-spoofing (FAS) systems. However, there are still no works to explore the fundamental natures (e.g., modality-aware inputs, suitable multimodal pre-training, and efficient fi...

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Bibliographic Details
Published in:	International journal of computer vision Vol. 132; no. 11; pp. 5217 - 5238
Main Authors:	Yu, Zitong, Cai, Rizhao, Cui, Yawen, Liu, Xin, Hu, Yongjian, Kot, Alex C.
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.11.2024 Springer Springer Nature B.V
Subjects:	Artificial Intelligence Classification Computer Imaging Computer Science Computer vision Computers Electric transformers Freezing Image Processing and Computer Vision Investigations Machine learning Pattern Recognition Pattern Recognition and Graphics Special Issue on Biometrics Security and Privacy Spoofing Vision Adaptive multimodal adapter Multimodal Masked autoencoder Face anti-spoofing
ISSN:	0920-5691, 1573-1405
Online Access:	Get full text
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