An automatic framework for creating high-fidelity 3D hair models that are suitable for use in downstream graphics applications. This approach utilizes real-world hair wigs as input, and is able to reconstruct hair strands for a wide range of hair styles. Systems and method leverage computed tomography (Cl) to create density volumes of the hair regions, allowing users to see through the hair unlike image-based approaches which are limited to reconstructing the visible surface. To address the noise and limited resolution of the input density volumes, we employ a coarse-to-fine approach. This process first recovers guide strands with estimated 3D orientation fields, and then populates dense strands through a novel neural interpolation of the guide strands. The generated strands are then refined to conform to the input density volumes.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.