Abstract
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
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
"HIGH-FIDELITY 3D HAIR MODELING USING COMPUTED TOMOGRAPHY", Technical Disclosure Commons, (January 17, 2024)
https://www.tdcommons.org/dpubs_series/6611