Synthesizing realistic profile faces is promising for more efficiently training deep pose-
invariant models for large-scale unconstrained face recognition, by populating samples with …

Synthesizing realistic profile faces is beneficial for more efficiently training deep pose-
invariant models for large-scale unconstrained face recognition, by augmenting the number …

Extreme pose variation is one of the key obstacles to accurate face recognition in practice.
Compared with current techniques for pose-invariant face recognition, which either expect …

Although deep learning techniques have achieved extraordinary accuracy in recognizing
human faces, the pose variances of images captured in real-world scenarios still hinder …

Face swapping, a study of editing the face identity attributes, has received more attention in
recent years due to the breakthrough progress of deep learning. Due to its application and …

Face-reenactment, also knows as puppetry, has become very popular in recent years. The
proposed task requires generating new face expression while preserving person identity …

Extreme pose variation is one of the key obstacles to accurate face recognition in practice.
Compared with current techniques for pose-invariant face recognition, which either expect …

In this paper, we present a novel approach for transferring shape and expression of a face in
image to that of another, regardless of variance between the two faces in illumination, color …