Implicit Face

Implicit face modeling uses neural networks to represent 3D facial geometry implicitly, offering advantages over traditional explicit methods like 3D Morphable Models. Current research focuses on improving the accuracy and detail of these implicit representations, often employing neural signed distance functions (SDFs) or incorporating anatomical constraints for enhanced realism and control. This approach is driving advancements in applications such as facial reenactment, high-fidelity 3D reconstruction from limited views, and efficient facial animation, impacting fields like film, virtual reality, and telepresence. The ability to generate highly realistic and controllable facial models from limited data is a key focus of ongoing work.