Over the last few months we’ve seen two new companies formed around the concept of providing tools based on deep learning for visual effects. The positive responses they’ve received so far already along with the multitude of opportunities in the field are sure to mean that they will be the first of many. Kognat aims…Read More
Month: June 2018
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