Fair and Accurate Age Prediction Using Distribution Aware Data Curation and Augmentation

Yushi Cao, David Berend, Palina Tolmach, Guy Amit, Moshe Levy, Yang Liu, Asaf Shabtai, Yuval Elovici

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Deep learning-based facial recognition systems have experienced increased media attention due to exhibiting unfair behavior. Large enterprises, such as IBM, shut down their facial recognition and age prediction systems as a consequence. Age prediction is an especially difficult application with the issue of fairness remaining an open research problem (e.g. predicting age for different ethnicity equally accurate). One of the main causes of unfair behavior in age prediction methods lies in the distribution and diversity of the training data. In this work, we present two novel approaches for dataset curation and data augmentation in order to increase fairness through balanced feature curation and increase diversity through distribution aware augmentation. To achieve this, we introduce out-of-distribution detection to the facial recognition domain which is used to select the data most relevant to the deep neural network's (DNN) task when balancing the data among age, ethnicity, and gender. Our approach shows promising results. Our best-trained DNN model outperformed all academic and industrial baselines in terms of fairness by up to 4.92 times and also enhanced the DNN's ability to generalise outperforming Amazon AWS and Microsoft Azure public cloud systems by 31.88% and 10.95%, respectively.
Original languageEnglish
Title of host publicationProceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2867-2877
Number of pages11
ISBN (Electronic)9781665409155
DOIs
StatePublished - 2022
Event22nd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022 - Waikoloa, United States
Duration: 4 Jan 20228 Jan 2022

Publication series

NameProceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022

Conference

Conference22nd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022
Country/TerritoryUnited States
CityWaikoloa
Period4/01/228/01/22

Keywords

  • Accountability
  • Deep Learning
  • Explainable AI
  • Face Processing
  • Fairness
  • Image Processing
  • Large-scale Vision Applications
  • Learning and Optimization
  • Privacy and Ethics in Vision Biometrics
  • Statistical Methods

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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