Attended End-to-End Architecture for Age Estimation From Facial Expression Videos

@article{Pei2020AttendedEA,
  title={Attended End-to-End Architecture for Age Estimation From Facial Expression Videos},
  author={Wenjie Pei and Hamdi Dibeklioğlu and Tadas Baltru{\vs}aitis and David M. J. Tax},
  journal={IEEE Transactions on Image Processing},
  year={2020},
  volume={29},
  pages={1972-1984}
}
The main challenges of age estimation from facial expression videos lie not only in the modeling of the static facial appearance, but also in the capturing of the temporal facial dynamics. Traditional techniques to this problem focus on constructing handcrafted features to explore the discriminative information contained in facial appearance and dynamics separately. This relies on sophisticated feature-refinement and framework-design. In this paper, we present an end-to-end architecture for age… Expand
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