High performance for face recognition systems occurs in controlled environments and
degrades with variations in illumination, facial expression, and pose. Efforts have been …

Age invariant face recognition (AIFR) is highly required in many applications like law
enforcement, national databases and security. Recognizing faces across aging is difficult …

Modeling the aging process of human face is important for cross-age face verification and
recognition. In this paper, we introduce a recurrent face aging (RFA) framework based on a …

One of the challenges in automatic face recognition is to achieve temporal invariance. In
other words, the goal is to come up with a representation and matching scheme that is …

We present an approach that takes a single photograph of a child as input and automatically
produces a series of age-progressed outputs between 1 and 80 years of age, accounting for …

In this paper, we present a compositional and dynamic model for face aging. The
compositional model represents faces in each age group by a hierarchical And-or graph, in …

In this paper, we aim to automatically render aging faces in a personalized way. Basically, a
set of age-group specific dictionaries are learned, where the dictionary bases corresponding …

Face verification in the presence of age progression is an important problem that has not
been widely addressed. In this paper, we study the problem by designing and evaluating …

Age progression is defined as aesthetically re-rendering the aging face at any future age for
an individual face. In this work, we aim to automatically render aging faces in a personalized …

Facial aging, a new dimension that has recently been added to the problem of face
recognition, poses interesting theoretical and practical challenges to the research …