Mesoscopic Facial Geometry Inference Using Deep Neural Networks

We present a learning-based approach for synthesizing facial geometry at medium and fine scales from diffusely-lit facial texture maps. When applied to an image sequence, the synthesized detail is temporally coherent. Unlike current state-of-the-art methods, which assume ”dark is deep”, our model is trained with measured facial detail collected using polarized gradient illumination in a…Read More

High-Fidelity Facial Reflectance and Geometry Inference From an Unconstrained Image

We present a deep learning-based technique to infer high-quality facial reflectance and geometry given a single unconstrained image of the sub- ject, which may contain partial occlusions and arbitrary illumination conditions. The reconstructed high-resolution textures, which are generated in only a few seconds, include high-resolution skin surface reflectance maps, representing both the diffuse and specular…Read More