We present a fully automatic approach to real-time
3D face reconstruction from monocular in-the-wild videos. With
the use of a cascaded-regressor based face tracking and a 3D
Morphable Face Model shape fitting, we obtain a semi-dense 3D
face shape. We further use the texture information from multiple
frames to build a holistic 3D face representation from the video
footage. Our system is able to capture facial expressions and
does not require any person-specific training. We demonstrate
the robustness of our approach on the challenging
300 Videos in
the Wild
(300-VW) dataset. Our real-time fitting framework is
available as an open source library at http://4dface.org.