DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control

Understand

Recent facial image synthesis methods have been mainly based on conditional generative models.

• Sketch-based conditions can effectively describe the geometry of faces, including the contours of facial components, hair structures, as well as salient edges (e.g., wrinkles) on face surfaces but lack effective control of appearance, which is influenced by color, material, lighting condition, etc.
• To have more control of generated results, one possible approach is to apply existing disentangling works to disentangle face images into geometry and appearance representations.
• However, existing disentangling methods are not optimized for human face editing, and cannot achieve fine control of facial details such as wrinkles.