Hybrid differentiable rendering for light transport simulation systems and applications
US12243152B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 14, 2024 |
| Grant date | Mar 4, 2025 |
| Priority date | — |
| Expiry date | Feb 14, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2219/2012
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In various examples, information may be received for a 3D model, such as 3D geometry information, lighting information, and material information. A machine learning model may be trained to disentangle the 3D geometry information, the lighting information, and/or material information from input data to provide the information, which may be used to project geometry of the 3D model onto an image plane to generate a mapping between pixels and portions of the 3D model. Rasterization may then use the mapping to determine which pixels are covered and in what manner, by the geometry. The mapping may also be used to compute radiance for points corresponding to the one or more 3D models using light transport simulation. Disclosed approaches may be used in various applications, such as image editing, 3D model editing, synthetic data generation, and/or data set augmentation.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.