公开(公告)号：US20240185506A1

公开(公告)日：2024-06-06

申请号：US18441486

申请日：2024-02-14

申请人： NVIDIA Corporation

发明人： Wenzheng Chen ,  Joey Litalien ,  Jun Gao ,  Zian Wang ,  Clement Tse Tsian Christophe Louis Fuji Tsang ,  Sameh Khamis ,  Or Litany ,  Sanja Fidler

IPC分类号： G06T15/06 ,  G06T15/50 ,  G06T19/20

CPC分类号： G06T15/06 ,  G06T15/506 ,  G06T19/20 ,  G06T2219/2012

摘要： 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.

公开(公告)号：US11922558B2

公开(公告)日：2024-03-05

申请号：US17826611

申请日：2022-05-27

申请人： NVIDIA Corporation

发明人： Wenzheng Chen ,  Joey Litalien ,  Jun Gao ,  Zian Wang ,  Clement Tse Tsian Christophe Louis Fuji Tsang ,  Sameh Khamis ,  Or Litany ,  Sanja Fidler

IPC分类号： G06T15/06 ,  G06T15/50 ,  G06T19/20

CPC分类号： G06T15/06 ,  G06T15/506 ,  G06T19/20 ,  G06T2219/2012

摘要： 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.

公开(公告)号：US20220383582A1

公开(公告)日：2022-12-01

申请号：US17826611

申请日：2022-05-27

申请人： NVIDIA Corporation

发明人： Wenzheng Chen ,  Joey Litalien ,  Jun Gao ,  Zian Wang ,  Clement Tse Tsian Christophe Louis Fuji Tsang ,  Sameh Khamis ,  Or Litany ,  Sanja Fidler

IPC分类号： G06T15/06 ,  G06T19/20 ,  G06T15/50

摘要： 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.