Abstract
The visual richness of computer graphics applications is frequently limited by the difficulty of obtaining high-quality, detailed 3D models. This paper proposes a method for realistically transferring details (specifically, displacement maps) from existing high-quality 3D models to simple shapes that may be created with easy-to-learn modeling tools. Our key insight is to use metric learning to find a combination of geometric features that successfully predicts detail-map similarities on the source mesh, and use the learned feature combination to drive the detail transfer. The latter uses a variant of multi-resolution non-parametric texture synthesis, augmented by a high-frequency detail transfer step in texture space. We demonstrate that our technique can successfully transfer details among a variety of shapes including furniture and clothing.
Video
Bibtex
@inproceddings{ Berkiten17,
author = "S. Berkiten, M. Halber, J. Solomon, C. Ma, H. Li, S. Rusinkiewicz",
title = "Learning Detail Transfer based on Geometric Features",
year = "2017" }
Materials
