Face Recognition Vendor Test (FRVT) - Performance of Automated Age Estimation Algorithms

By Mei Ngan, Patrick Grother. 2014

23 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Hu Han
2. Anil K. Jain
3. Xiaoming Liu
4. Arun A. Ross
5. Xiaogang Wang
6. Sébastien Marcel
7. Amin Jourabloo
8. Yaojie Liu

In Evaluation & Benchmarks

1. Emily Bello-Pardo
2. Hu Han
3. Anil K. Jain

Citations in the corpus

• Diagnosing Gender Bias in Image Recognition Systems (2020, background): “Finally, as studies have shown that the performance of image recognition algorithms may depend upon the age of individuals in the images (Ngan and Grother 2014; Michalski 2017), we control for age (see the Online Appendix).”
• Age , Gender and Race Estimation from Unconstrained Face Images (2014, background): “While stateof-the-art demographic estimation methods are able to attain a mean absolute error (MAE) of about 4 years for age estimation1, and more than 95% accuracy for gender and race classifications, most of these studies have utilized face images captured in rather controlled sensing and cooperat”