التفاصيل البيبلوغرافية
| العنوان: |
Soft-Ranking Label Encoding for Robust Facial Age Estimation |
| المؤلفون: |
Xusheng Zeng, Junyang Huang, Changxing Ding |
| المصدر: |
IEEE Access, Vol 8, Pp 134209-134218 (2020) |
| بيانات النشر: |
IEEE, 2020. |
| سنة النشر: |
2020 |
| المجموعة: |
LCC:Electrical engineering. Electronics. Nuclear engineering |
| مصطلحات موضوعية: |
Age estimation, age encoding, facial attribute analysis, Electrical engineering. Electronics. Nuclear engineering, TK1-9971 |
| الوصف: |
Automatic facial age estimation can be used in a wide range of real-world applications. However, this process is challenging due to the randomness and slowness of the aging process. Accordingly, in this paper, we propose a novel method aimed at overcoming the challenges associated with facial age estimation. First, we propose a novel age encoding method, referred to as `Soft-ranking', which encodes two important properties of facial age, i.e., the ordinal property and the correlation between adjacent ages. Therefore, Soft-ranking provides a richer supervision signal for training deep models. Moreover, we carefully analyze existing evaluation protocols for age estimation, finding that the overlap in identity between the training and testing sets affects the relative performance of different age encoding methods. Moreover, we achieve state-of-the-art performance on four most popular age databases, i.e., Morph II, AgeDB, CLAP2015, and CLAP2016. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2169-3536 |
| Relation: |
https://ieeexplore.ieee.org/document/9145576/; https://doaj.org/toc/2169-3536 |
| DOI: |
10.1109/ACCESS.2020.3010815 |
| URL الوصول: |
https://doaj.org/article/477bcc911330422d811b5a422b9ad7cc |
| رقم الانضمام: |
edsdoj.477bcc911330422d811b5a422b9ad7cc |
| قاعدة البيانات: |
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