A fast mask synthesis method for face recognition-Reference-Cited by-同舟云学术

A fast mask synthesis method for face recognition

Published:2024-08-14 Issue:1 Volume:2 Page:
ISSN:2731-9008
Container-title:Visual Intelligence
language:en
Short-container-title:Vis. Intell.

Author:

Guo Kaiwen^ORCID,Zhao Chaoyang,Wang Jinqiao

Abstract

AbstractMask face recognition has recently gained increasing attention in the current context. Face mask occlusion seriously affects the performance of face recognition systems, because more than 75% of the face area remains unexposed and the mask directly causes an increase in intra-class differences and a decrease in inter-class separability in the feature space. To improve the performance of face recognition model against mask occlusion, we propose a fast and efficient method for mask generation in this paper, which can avoid the need for large-scale collection of real-world mask face training sets. This approach can be embedded in the training process of any mask face model as a module and is very flexible. Experiments on the MLFW, MFR2 and RMFD datasets show the effectiveness and flexibility of our approach that outperform the state-of-the-art methods.

Funder

National Natural Science Foundation of China

Natural Science Foundation for Young Scientists of Shanxi Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s44267-024-00060-z.pdf

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