  This paper presents a novel approach for synthesizing facial affect, which is
based on our annotating 600,000 frames of the 4DFAB database in terms of
valence and arousal. The input of this approach is a pair of these emotional
state descriptors and a neutral 2D image of a person to whom the corresponding
affect will be synthesized. Given this target pair, a set of 3D facial meshes
is selected, which is used to build a blendshape model and generate the new
facial affect. To synthesize the affect on the 2D neutral image, 3DMM fitting
is performed and the reconstructed face is deformed to generate the target
facial expressions. Last, the new face is rendered into the original image.
Both qualitative and quantitative experimental studies illustrate the
generation of realistic images, when the neutral image is sampled from a
variety of well known databases, such as the Aff-Wild, AFEW, Multi-PIE,
AFEW-VA, BU-3DFE, Bosphorus.
