Cache Points For Production-Scale Occlusion-Aware Many-Lights Sampling And Volumetric Scattering

Yining Karl Li, Charlotte Zhu, Gregory Nichols, Peter Kutz, Wei-Feng Wayne Huang, David Adler, Brent Burley, and Daniel Teece

DigiPro '24: Proceedings of the Digital Production Symposium 2024. Article No. 6

A production scene from Us Again containing 4881396 light sources (analytical lights, emissive triangles, and emissive volumes), rendered using 32 samples per pixel with uniform light selection (a), locally optimal light selection (b), and our cache points system (c). Uniform light selection produces a faster result but converges poorly, while building a locally optimal light distribution per path vertex produces a more converged result but is much slower. Our cache points system (c) produces a noise level similar to (b) while maintaining performance closer to (a). To clearly show noise differences, this figure does not include the post-renderer compositing that is present in the final production frame.

Abstract

A hallmark capability that defines a renderer as a production renderer is the ability to scale to handle scenes with extreme complexity, including complex illumination cast by a vast number of light sources. In this paper, we present Cache Points, the system used by Disney’s Hyperion Renderer to perform efficient unbiased importance sampling of direct illumination in scenes containing up to millions of light sources. Our cache points system includes a number of novel features. We build a spatial data structure over points that light sampling will occur from instead of over the lights themselves. We do online learning of occlusion and factor this into our importance sampling distribution. We also accelerate sampling in difficult volume scattering cases.

Over the past decade, our cache points system has seen extensive production usage on every feature film and animated short produced by Walt Disney Animation Studios, enabling artists to design lighting environments without concern for complexity. In this paper, we will survey how the cache points system is built, works, impacts production lighting and artist workflows, and factors into the future of production rendering at Disney Animation.

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Text Reference

Yining Karl Li, Charlotte Zhu, Gregory Nichols, Peter Kutz, Wei-Feng Wayne Huang, David Adler, Brent Burley, and Daniel Teece. Cache Points For Production-Scale Occlusion-Aware Many-Lights Sampling And Volumetric. DigiPro '24: Proceedings of the Digital Production Symposium 2024. Article 6, July 2024.

Bibtex Reference

@inproceedings{li24cachepoints,
	author    = {Li, Yining Karl and Zhu, Charlotte and Nichols, Gregory and Kutz, Peter and Huang, Wei-Feng Wayne and 
		     Adler, David and Burley, Brent and Teece, Daniel},
	title     = {Cache Points For Production-Scale Occlusion-Aware Many-Lights Sampling And Volumetric},
	booktitle = {DigiPro '24: Proceedings of the Digital Production Symposium 2024},
	month     = jul,
	year      = {2024},
	articleno = {6},
	doi       = {10.1145/3665320.3670993},
	keywords  = {path tracing, global illumination, light selection, importance sampling, volume rendering},
}

Acknowledgements

The techniques presented in this paper have seen continual improvement over the years, with many contributions made by both current and past members of the Hyperion development team. In addition to the authors, other past key contributors to the cache points system include Patrick Kelly, Ralf Habel, Ben Spencer, Benedikt Bitterli, and Matt Jen-Yuan Chiang. The authors are also thankful to Mackenzie Thompson, Andrew Bauer, Brian Green, Mark Lee, and Lea Reichardt from the Hyperion development team for their support of and feedback on this paper.

We thank Jan Novák, Marios Papas and Thomas Müller from Disney Research|Studios and Cliff Ramshaw and Julian Fong from Pixar’s RenderMan development team for interesting and helpful discussions on the topics of many-lights sampling and volumetric scattering through optically thin media. We also thank Ivo Kondapa- neni for his work implementing Vevoda et al. 2018’s technique in an experimental branch of Hyperion, which has served as a useful comparison point. We are also thankful to our anonymous paper referees for their invaluable feedback.

Finally, we are especially grateful to the many artists and technical directors that have used Hyperion and whose feedback, suggestions, and partnership over the years have influenced and shaped every aspect of the renderer, including the cache points system presented in this paper.