HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details

Understand

3D Morphable Models (3DMMs) demonstrate great potential for reconstructing faithful and animatable 3D facial surfaces from a single image.

• The facial surface is influenced by the coarse shape, as well as the static detail (e,g., person-specific appearance) and dynamic detail (e.g., expression-driven wrinkles).
• Previous work struggles to decouple the static and dynamic details through image-level supervision, leading to reconstructions that are not realistic.
• In this paper, we aim at high-fidelity 3D face reconstruction and propose HiFace to explicitly model the static and dynamic details.