We present a novel approach to reconstruct high-fidelity geometric
human face model from a single RGB image. The main idea is to
add details into a coarse 3D Morphable Model (3DMM) based model
in a self-supervised way. Our observation is that most of the facial
details like wrinkles are driven by expression and intrinsic facial
characteristics which here we refer to as the facial attribute. To this
end, we propose an expression related details recovery scheme and
a facial attribute representation.