Creating fine garment details requires significant efforts and huge
computational resources. In contrast, a coarse shape may be easy to acquire in
many scenarios (e.g., via low-resolution physically-based simulation, linear
blend skinning driven by skeletal motion, portable scanners). In this paper, we
show how to enhance, in a data-driven manner, rich yet plausible details
starting from a coarse garment geometry. Once the parameterization of the
garment is given, we formulate the task as a style transfer problem over the
space of associated normal maps. In order to facilitate generalization across
garment types and character motions, we introduce a patch-based formulation,
that produces high-resolution details by matching a Gram matrix based style
loss, to hallucinate geometric details (i.e., wrinkle density and shape). We
extensively evaluate our method on a variety of production scenarios and show
that our method is simple, light-weight, efficient, and generalizes across
underlying garment types, sewing patterns, and body motion.Comment: 12 page
