FACE TEXTURE GENERATION AND IDENTITY-PRESERVING RECTIFICATION

Textures are a vital asset in conveying a realistic impression of a 3D scene to the viewers. In order to obtain high-quality textures, real-life objects are scanned or designers create handcrafted textures. Both tasks involve manual work, are quite time-consuming, and therefore fail when a large quantity of textures is required. Thus, we propose to use a Generative Adversarial Network to generate an artificial texture. As textures need to be perfectly aligned with the 2D projection of the 3D model, our method involves a texture rectification technique, ensuring that the generated textures wrap well onto the 3D model. On the example of face textures, we illustrate that our method generates textures of high quality and variance. Moreover, we show that the rectification process preserves the facial appearance and identity, indicating that we successfully disentangle features responsible for facial appearance and the texture’s fit.