JAM: A Comprehensive Model for Age Estimation, Verification, and Comparability

François David, Alexey A. Novikov, Ruslan Parkhomenko, Artem Voronin, Alix Melchy
10/5/2024
cs.CVcs.AI

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Abstract

This paper introduces a comprehensive model for age estimation, verification, and comparability, offering a comprehensive solution for a wide range of applications. It employs advanced learning techniques to understand age distribution and uses confidence scores to create probabilistic age ranges, enhancing its ability to handle ambiguous cases. The model has been tested on both proprietary and public datasets and compared against one of the top-performing models in the field. Additionally, it has recently been evaluated by NIST as part of the FATE challenge, achieving top places in many categories.

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Cite this paper

@article{david2024jam,
  title  = {JAM: A Comprehensive Model for Age Estimation, Verification, and Comparability},
  author = {François David and Alexey A. Novikov and Ruslan Parkhomenko and Artem Voronin and Alix Melchy},
  year   = {2024},
  eprint = {2410.04012},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2410.04012v2}
}

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