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Face Aging has raised considerable attentions and interest from the computervision community in recent years. Numerous approaches ranging from purely imageprocessing techniques to deep learning structures have been proposed inliterature. In this paper, we aim to give a review of recent developments ofmodern deep learning based approaches, i.e. Deep Generative Models, for FaceAging task. Their structures, formulation, learning algorithms as well assynthesized results are also provided with systematic discussions. Moreover,the aging databases used in most methods to learn the aging process are alsoreviewed.

Longitudinal Face Aging in the Wild - Recent Deep Learning Approaches