Recently, generative adversarial networks (GANs) have progressed enormously, which
makes them able to learn complex data distributions in particular faces. More and more …

Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

Facial editing is an important task in vision and graphics with numerous applications.
However, existing works are incapable to deliver a continuous and fine-grained editing …

The task of age transformation illustrates the change of an individual's appearance over
time. Accurately modeling this complex transformation over an input facial image is …

The world we see is ever-changing and it always changes with people, things, and the
environment. Domain is referred to as the state of the world at a certain moment. A research …

Generative Adversarial Networks (GANs) have achieved impressive results in various image
synthesis tasks, and are becoming a hot topic in computer vision research because of the …

To minimize the effects of age variation in face recognition, previous work either extracts
identity-related discriminative features by minimizing the correlation between identity-and …

A large number of intelligent models for masked face recognition (MFR) has been recently
presented and applied in various fields, such as masked face tracking for people safety or …

Since photorealistic faces can be readily generated by facial manipulation technologies
nowadays, potential malicious abuse of these technologies has drawn great concerns …

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 …