Patent · US Active

Learning neural reflectance shaders from images

US11972519B2 · kind B2 · utility

0Cited by

0References

20Claims

0Family size

Assignee

Intel Corporation · US

Inventors

Benjamin Ummenhofer · Unterhaching, DE
Shenlong Wang · Toronto, CA
Sanskar Agrawal · Pennington, US
Yixing Lao · Santa Clara, US
Kai Zhang · Shanghai, CN
Stephan Richter · Neubiberg, DE
Vladlen Koltun · Santa Clara, US

Key dates

Filing date	Jun 24, 2022
Grant date	Apr 30, 2024
Priority date	—
Expiry date	Nov 11, 2042

Classification

Technology area (CPC G)Physics
CPC primaryG06T2210/52
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

Described herein are techniques for learning neural reflectance shaders from images. A set of one or more machine learning models can be trained to optimize an illumination latent code and a set of reflectance latent codes for an object within a set of input images. A shader can then be generated based on a machine learning model of the one or more machine learning models. The shader is configured to sample the illumination latent code and the set of reflectance latent codes for the object. A 3D representation of the object can be rendered using the generated shader.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.