  The existing auto-encoder based face pose editing methods primarily focus on
modeling the identity preserving ability during pose synthesis, but are less
able to preserve the image style properly, which refers to the color,
brightness, saturation, etc. In this paper, we take advantage of the well-known
frontal/profile optical illusion and present a novel two-stage approach to
solve the aforementioned dilemma, where the task of face pose manipulation is
cast into face inpainting. By selectively sampling pixels from the input face
and slightly adjust their relative locations with the proposed ``Pixel
Attention Sampling" module, the face editing result faithfully keeps the
identity information as well as the image style unchanged. By leveraging
high-dimensional embedding at the inpainting stage, finer details are
generated. Further, with the 3D facial landmarks as guidance, our method is
able to manipulate face pose in three degrees of freedom, i.e., yaw, pitch, and
roll, resulting in more flexible face pose editing than merely controlling the
yaw angle as usually achieved by the current state-of-the-art. Both the
qualitative and quantitative evaluations validate the superiority of the
proposed approach.
