Nvidia Corporation

Clement Tse Tsian Christophe Louis Fuji Tsang

Sanja Fidler

Jun Gao

Wenzheng Chen

Or Litany

Joey Litalien

Zian Wang

Sameh Khamis

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.

Hybrid differentiable rendering for light transport simulation systems and applications

Growing community of inventors

Toronto, Canada

Clement Tse Tsian Christophe Louis Fuji Tsang