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Survey: Machine Learning in Production Rendering

Graphics 2020-05-27 v1 Machine Learning

Abstract

In the past few years, machine learning-based approaches have had some great success for rendering animated feature films. This survey summarizes several of the most dramatic improvements in using deep neural networks over traditional rendering methods, such as better image quality and lower computational overhead. More specifically, this survey covers the fundamental principles of machine learning and its applications, such as denoising, path guiding, rendering participating media, and other notoriously difficult light transport situations. Some of these techniques have already been used in the latest released animations while others are still in the continuing development by researchers in both academia and movie studios. Although learning-based rendering methods still have some open issues, they have already demonstrated promising performance in multiple parts of the rendering pipeline, and people are continuously making new attempts.

Keywords

Cite

@article{arxiv.2005.12518,
  title  = {Survey: Machine Learning in Production Rendering},
  author = {Shilin Zhu},
  journal= {arXiv preprint arXiv:2005.12518},
  year   = {2020}
}

Comments

This was the survey I did for my PhD research exam

R2 v1 2026-06-23T15:48:37.734Z