Cycles has supported path-traced subsurface scattering for a while, but while it's
more accurate than other approaches, the increase in noise makes it an expensive option.
To improve this, this patch implements Dwivedi guiding, a technique that is based on
zero-variance random walk theory from particle physics and helps to produce shorter
random walks with more consistent throughput.
The idea behind this is that in non-white materials, each scattering event inside the
medium reduces the path throughput. Therefore, the darker the material is, the lower the
contribution of paths that travel far from the origin is.
In order to reduce variance, Dwivedi guiding uses modified direction and distance sampling
functions that favor paths which go back towards the medium interface.
By carefully selecting these sampling distributions, variance can be greatly reduced, and
as a neat side effect shorter paths are produced, which speeds up the process.
One limitation of just blindly applying this is that the guiding is derived from the
assumption of a medium that covers an infinite half-space. Therefore, at corners or thin
geometry where this does not hold, the algorithm might lead to fireflies.
To avoid this, the implementation here uses MIS to combine the classic and guided sampling.
Since each of those works on one of the three color channels, the final estimator combines
six sampling techniques. This results in some unintuitive math, but I tried to structure
it in a way that makes some sense.
Another improvement is that in areas where the other side of the mesh is close (e.g. ears),
the algorithm has a chance to switch to guiding towards the other side. This chance is based
on how deep the random walk is inside the object, and once again MIS is applied to the
decision, giving a total of nine techniques.
Combining all this, the noise of path-traced subsurface scattering is reduced significantly.
In my testing with the Rain character model and a simple lighting setup, the path-traced
SSS is now actually less noisy than the Christensen-Burley approximation at same render time
while of course still being significantly more realistic.
Differential Revision: https://developer.blender.org/D9932
2f6d62bf88