Laser & Optoelectronics Progress, Volume. 60, Issue 10, 1010019(2023)

Transformer for Age-Invariant Face Recognition

Cheng Liu1, Liangcai Cao2, Ye Jin3, Haowei Wang3, and Songfeng Yin1、*
Author Affiliations
  • 1Hefei Institute for Public Safety Research, Tsinghua University, Hefei 230601, Anhui , China
  • 2State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing 100084, China
  • 3Criminal Police Detachment of Hefei Public Security Bureau, Hefei 230601, Anhui , China
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    References(14)

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    [2] Deng J K, Guo J, Xue N N et al. ArcFace: additive angular margin loss for deep face recognition[C], 4685-4694(2019).

    [4] Wang H, Gong D H, Li Z F et al. Decorrelated adversarial learning for age-invariant face recognition[C], 3522-3531(2019).

    [5] He X C, Guo Y, Li Q L et al. Age invariant face recognition based on deep learning[J]. Acta Automatica Sinica, 48, 877-886(2022).

    [6] Sun W B, Wang R, Sun L Z et al. Deep learning for cross-age face recorgnition[J]. Laser & Optoelectronics Progress, 59, 0215001(2022).

    [7] Huang Z Z, Zhang J P, Shan H M. When age-invariant face recognition meets face age synthesis: a multi-task learning framework[C], 7278-7287(2021).

    [13] Moschoglou S, Papaioannou A, Sagonas C et al. AgeDB: the first manually collected, in-the-wild age database[C], 1997-2005(2017).

    [14] Chen B C, Chen C S, Hsu W H. Face recognition and retrieval using cross-age reference coding with cross-age celebrity dataset[J]. IEEE Transactions on Multimedia, 17, 804-815(2015).

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    Cheng Liu, Liangcai Cao, Ye Jin, Haowei Wang, Songfeng Yin. Transformer for Age-Invariant Face Recognition[J]. Laser & Optoelectronics Progress, 2023, 60(10): 1010019

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    Paper Information

    Category: Image Processing

    Received: Feb. 22, 2022

    Accepted: Apr. 6, 2022

    Published Online: May. 10, 2023

    The Author Email: Songfeng Yin (yinsongfeng@tsinghua-hf.edu.cn)

    DOI:10.3788/LOP220785

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