Over the last few years, increased interest has arisen with respect to age-related tasks in the
Computer Vision community. As a result, several" in-the-wild" databases annotated with …

The two underlying requirements of face age progression, ie aging accuracy and identity
permanence, are not well studied in the literature. In this paper, we present a novel …

We address the problem of single photo age progression and regression—the prediction of
how a person might look in the future, or how they looked in the past. Most existing aging …

Since it is difficult to collect face images of the same subject over a long range of age span,
most existing face aging methods resort to unpaired datasets to learn age map**s …

Face aging is to render a given face to predict its future appearance, which plays an
important role in the information forensics and security field as the appearance of the face …

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 …

Semantic segmentation aims to predict pixel-level labels. It has become a popular task in
various computer vision applications. While fully supervised segmentation methods have …

Facial Attribute Manipulation (FAM) aims to aesthetically modify a given face image to
render desired attributes, which has received significant attention due to its broad practical …

Deep neural networks have been widely used in numerous computer vision applications,
particularly in face recognition. However, deploying deep neural network face recognition on …

Modeling the long-term facial aging process is extremely challenging due to the presence of
large and non-linear variations during the face development stages. In order to efficiently …