A list of path tracing shaders

I have gathered a list of path tracing shaders on ShaderToy.

Path tracing is a surprisingly simple technique to render realistic images. This would be my definition if you are unfamiliar with the term. But if you already have experience with various ray tracing techniques, I would probably say that path tracing is a remarkably elegant solution to the rendering equation. You can implement a toy path tracer in a weekend or, if you’ve already done it a few times before, within 25 minutes.

Recently I was documenting myself on path tracing, and some of the techniques that can be used, like next event estimation, bidirectional path tracing, Russian roulette, etc. This is a case where ShaderToy can be an invaluable source of examples and information, and so I was browsing path tracing shaders there. As the number of open tabs was starting to get impractical, I decided to use the “playlist” feature of ShaderToy to bookmark them all.

You can find the list here: Path tracing, on ShaderToy.

The examples of path tracers listed include very naive implementations, hacky ones, rendering features like advanced BRDF, volumetric lighting or spectral rendering, or various noise reduction techniques such as next event estimation, bidirectional path tracing, multiple importance sampling, accumulation over frames with temporal reprojection, screen space blue noise, or convolutional neural network based denoising.

Some of those shaders are meant to be artworks, but even the technical experimentation ones look nice, because the global illumination inherent to path tracing tends to generate images that are pretty.

Screenshot of the list on ShaderToy, with various kinds of path tracers visible.

Practical Pigment Mixing for Digital Painting

About a year ago at SIGGRAPH Asia 2021 (which took place as a hybrid conference both online and on site at the Tokyo International Forum) one of the technical papers that caught my attention was the publication by Šárka Sochorová and Ondřej Jamriška on color mixing.

Color mixing in most digital painting tools is infamously unsatisfying, often limited to a linear interpolation in RBG space, resulting in unpleasing gradients very different from what one would expect. Ten years ago I mentioned this article that presented the color mixing of the application Paper, which tried to solve this very problem.

This time, the core idea is to model colors as pigments: estimate the pigment concentration based on the color, so in a way, move from RGB space to “pigment space”, and interpolate the pigment concentration, before converting back to RGB space.

The paper uses the Kubelka-Munk model for estimating colors from pigment concentration. The problem however is to find a transformation between the two spaces. A first assumption is made on the available pigments: essentially restricting them to CMYK. Then two problems are addressed: RGB colors that cannot be represented with those pigments, and likewise pigment colors that cannot be represented in RGB.
The paper proposes a remapping that enables a transform and its inverse, thus allowing to move from RGB space to pigment space, interpolate in pigment space, and move back to RGB space.

You could argue this is therefore a physically based diffuse color mixing.

Finally, the implementation of the proposed model, Mixbox, is available under a CC BY-NC license:

Two Minute Papers did a video on this paper as well: