  Facial Expressions induce a variety of high-level details on the 3D face
geometry. For example, a smile causes the wrinkling of cheeks or the formation
of dimples, while being angry often causes wrinkling of the forehead. Morphable
Models (3DMMs) of the human face fail to capture such fine details in their
PCA-based representations and consequently cannot generate such details when
used to edit expressions. In this work, we introduce FaceDet3D, a
first-of-its-kind method that generates - from a single image - geometric
facial details that are consistent with any desired target expression. The
facial details are represented as a vertex displacement map and used then by a
Neural Renderer to photo-realistically render novel images of any single image
in any desired expression and view. The project website is:
http://shahrukhathar.github.io/2020/12/14/FaceDet3D.html
