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Authors: Yan Yang Aaren ; George Bebis and Mircea Nicolescu

Affiliation: Department of Computer Science and Engineering, University of Nevada, Reno, 1664 N Virginia St, Reno, NV 89557, U.S.A.

Keyword(s): Generative Adversarial Networks, Data Augmentation, Face Recognition.

Abstract: The COVID-19 spread raised urgent requirements for masked face recognition and detection tasks. However, the current masked face datasets are insufficient. To alleviate the limitation of data, we proposed a two-step data augmentation that combines rule-based mask warping with unpaired image-to-image translation. Our qualitative evaluations showed that our method achieved noticeable improvements compared to the rule-based warping alone and complemented results from other state-of-the-art GAN-based generation methods, such as IAMGAN. The non-mask change loss and the noise input we used to improve training showed effectiveness. We also provided an analysis of potential future directions based on observations of our experiments.

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Paper citation in several formats:
Aaren, Y.; Bebis, G. and Nicolescu, M. (2022). Two-step Data Augmentation for Masked Face Detection and Recognition: Turning Fake Masks to Real. In Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE; ISBN 978-989-758-563-0; ISSN 2795-4943, SciTePress, pages 126-134. DOI: 10.5220/0011037900003209

@conference{improve22,
author={Yan Yang Aaren. and George Bebis. and Mircea Nicolescu.},
title={Two-step Data Augmentation for Masked Face Detection and Recognition: Turning Fake Masks to Real},
booktitle={Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE},
year={2022},
pages={126-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011037900003209},
isbn={978-989-758-563-0},
issn={2795-4943},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE
TI - Two-step Data Augmentation for Masked Face Detection and Recognition: Turning Fake Masks to Real
SN - 978-989-758-563-0
IS - 2795-4943
AU - Aaren, Y.
AU - Bebis, G.
AU - Nicolescu, M.
PY - 2022
SP - 126
EP - 134
DO - 10.5220/0011037900003209
PB - SciTePress

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