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Age-invariant face network (AFN): a discriminative model towards age-invariant face recognition

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Abstract

Age-invariant face recognition (AIFR) is a significant research task in general face recognition, and it aims at eliminating gradual discordance of individual’s facial appearance caused by aging process. Previous discriminative methods decompose facial components over one-dimensional feature vectors which overlooks critical facial information and hypothesize linear relationships over aging process which is inadequate to describe complex correlations. In this paper, we propose an enhanced AIFR model, namely age-invariant face network (AFN), to eliminate the discrepancy of aging process over facial semblance. Specifically, we propose attentive factorization module (AFM) leveraging attention mechanism to decompose facial features into identity-related features and age-related features in two-dimensional space on both local and contextual levels. We take both linear and nonlinear correlation analyses into account for a better reflection of aging/rejuvenation process and hence propose a hybrid correlation regularizer (HCR) to supervise the decorrelation between factorized features. Both identity features and age features are supervised simultaneously in a multi-task learning framework where only identity features are used in test phase for evaluation of AIFR performance. Experiments across common cross-age datasets (e.g., FG-Net, CACD-VS, CALFW, AgeDB-30) show the effectiveness of proposed AFN. Further, our proposed AFN is validated over LFW dataset to demonstrate its effectiveness on general face recognition task.

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Acknowledgements

This work was supported by the National Key Research and Development Program of China (2019YFB2204200) and National Natural Science Foundation of China (U1832217).

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Authors and Affiliations

  1. Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China

    Jiarui Li, Li Zhou & Jie Chen

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Jiarui Li

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  1. Jiarui Li
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  2. Li Zhou
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Li, J., Zhou, L. & Chen, J. Age-invariant face network (AFN): a discriminative model towards age-invariant face recognition. Neural Comput & Applic (2024). https://doi.org/10.1007/s00521-024-09752-5

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