Survey: Machine Learning in Production Rendering

05/26/2020
by   Shilin Zhu, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/23/2020

Anecdotal Survey of Variations in Path Stroking among Real-world Implementations

Stroking a path is one of the two basic rendering operations in vector g...
research
11/15/2022

Foveated Rendering: a State-of-the-Art Survey

Recently, virtual reality (VR) technology has been widely used in medica...
research
06/22/2020

Differentiable Rendering: A Survey

Deep neural networks (DNNs) have shown remarkable performance improvemen...
research
12/23/2020

ANR: Articulated Neural Rendering for Virtual Avatars

The combination of traditional rendering with neural networks in Deferre...
research
02/22/2021

Data to Physicalization: A Survey of the Physical Rendering Process

Physical representations of data offer physical and spatial ways of look...
research
04/25/2020

Deep Photon Mapping

Recently, deep learning-based denoising approaches have led to dramatic ...
research
05/12/2023

Progressive Material Caching

The evaluation of material networks is a relatively resource-intensive p...

Please sign up or login with your details

Forgot password? Click here to reset