  Modeling the geometry and the appearance of knitted fabrics has been
challenging due to their complex geometries and interactions with light.
  Previous surface-based models have difficulties capturing fine-grained knit
geometries; Micro-appearance models, on the other hands, typically store
individual cloth fibers explicitly and are expensive to be generated and
rendered.
  Further, neither of the models have been matched the photographs to capture
both the reflection and the transmission of light simultaneously.
  In this paper, we introduce an efficient technique to generate knit models
with user-specified knitting patterns.
  Our model stores individual knit plies with fiber-level detailed depicted
using normal and tangent mapping.
  We evaluate our generated models using a wide array of knitting patterns.
Further, we compare qualitatively renderings to our models to photos of real
samples.
