Face age synthesis: A review on datasets, methods, and open research areas

Kale A., ALTUN O.

Pattern Recognition, cilt.143, 2023 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 143
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1016/j.patcog.2023.109791
  • Dergi Adı: Pattern Recognition
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, BIOSIS, Compendex, Computer & Applied Sciences, INSPEC, MLA - Modern Language Association Database, zbMATH
  • Anahtar Kelimeler: Age progression, Age regression, Face aging, GANs
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Face age synthesis is the determination of how a person looks in the future or the past by reconstructing their facial image. Determining the change in the human face over the years is a critical process for cross-age face recognition systems in forensic issues such as finding missing people and fugitive criminals. Therefore, it is a subject that has attracted attention in recent years. With the implementation of deep learning methods, better quality and photo-realistic images began to be produced. However, researchers continue to improve both aging accuracy and identity preservation requirements. We group the studies in the literature under two categories: classical methods and deep learning methods. We review both categories in the methods used, evaluation methods, and databases.