Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Multiple-Scattering Solutions for Sphere-Tracing of Volumetric
  Subsurface Effects   Accurate subsurface scattering solutions require the integration of optical
material properties along many complicated light paths. We present a method
that learns a simple geometric approximation of random paths in a homogeneous
volume of translucent material. The generated representation allows determining
the absorption along the path as well as a direct lighting contribution, which
is representative of all scattering events along the path. A sequence of
conditional variational auto-encoders (CVAEs) is trained to model the
statistical distribution of the photon paths inside a spherical region in
presence of multiple scattering events. A first CVAE learns to sample the
number of scattering events, occurring on a ray path inside the sphere, which
effectively determines the probability of the ray being absorbed. Conditioned
on this, a second model predicts the exit position and direction of the light
particle. Finally, a third model generates a representative sample of photon
position and direction along the path, which is used to approximate the
contribution of direct illumination due to in-scattering. To accelerate the
tracing of the light path through the volumetric medium toward the solid
boundary, we employ a sphere-tracing strategy that considers the light
absorption and is able to perform statistically accurate next-event estimation.
We demonstrate efficient learning using shallow networks of only three layers
and no more than 16 nodes. In combination with a GPU shader that evaluates the
CVAEs' predictions, performance gains can be demonstrated for a variety of
different scenarios. A quality evaluation analyzes the approximation error that
is introduced by the data-driven scattering simulation and sheds light on the
major sources of error in the accelerated path tracing process.

0
The categories of this paper are: hep-ph
8
The categories of this paper are: hep-ex
21
The categories of this paper are: adap-org
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
5
The categories of this paper are: gr-qc
10
The categories of this paper are: q-bio
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
19
The categories of this paper are: eess