Personalized and Occupational-aware Age Progression by Generative Adversarial Networks

Understand

Face age progression, which aims to predict the future looks, is important for various applications and has been received considerable attentions.

• Existing methods and datasets are limited in exploring the effects of occupations which may influence the personal appearances.
• In this paper, we firstly introduce an occupational face aging dataset for studying the influences of occupations on the appearances.
• It includes five occupations, which enables the development of new algorithms for age progression and facilitate future researches.