To minimize the impact of age variation on face recognition, age-invariant face recognition
(AIFR) extracts identity-related discriminative features by minimizing the correlation between …

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 …

Many studies have been conducted in the field of face aging, from approaches that use pure
image-processing algorithms, to those that use generative adversarial networks. In this …

The objective of face aging is to generate facial images that present the effects of aging. The
existing one-hot encoding method for aging and/or rejuvenation patterns overlooks the …

In this work, we propose a deep learning-based adversarial network for human face aging
synthesis. We use an image dataset consisting of young (Domain X) and elderly (Domain Y) …

Age transformation has an important role in criminal investigation, face recognition and other
fields. Common age transformation methods need to use pairs of datasets with age …