公开(公告)号：US20240020897A1

公开(公告)日：2024-01-18

申请号：US17862818

申请日：2022-07-12

Applicant: Nvidia Corporation

Inventor： Ting-Chun Wang ,  Ming-Yu Liu ,  Koki Nagano ,  Sameh Khamis ,  Jan Kautz

IPC: G06T11/60 ,  G06T5/00

CPC classification number: G06T11/60 ,  G06T5/006 ,  G06T2207/20084

Abstract: Apparatuses, systems, and techniques are presented to generate image data. In at least one embodiment, one or more neural networks are used to cause a lighting effect to be applied to one or more objects within one or more images based, at least in part, on synthetically generated images of the one or more objects.

公开(公告)号：US20230035306A1

公开(公告)日：2023-02-02

申请号：US17382027

申请日：2021-07-21

Applicant: Nvidia Corporation

Inventor： Ming-Yu Liu ,  Koki Nagano ,  Yeongho Seol ,  Jose Rafael Valle Gomes da Costa ,  Jaewoo Seo ,  Ting-Chun Wang ,  Arun Mallya ,  Sameh Khamis ,  Wei Ping ,  Rohan Badlani ,  Kevin Jonathan Shih ,  Bryan Catanzaro ,  Simon Yuen ,  Jan Kautz

IPC: G06T13/40 ,  H04N19/597 ,  G06N3/04 ,  G10L13/04 ,  G06T9/00 ,  G06T17/10 ,  G06T13/20

Abstract: Apparatuses, systems, and techniques are presented to generate media content. In at least one embodiment, a first neural network is used to generate first video information based, at least in part, upon voice information corresponding to one or more users, and a second neural network is used to generate second video information corresponding to the one or more users based, at least in part, upon the first video information and one or more images corresponding to the one or more users

公开(公告)号：US20220383582A1

公开(公告)日：2022-12-01

申请号：US17826611

申请日：2022-05-27

Applicant: NVIDIA Corporation

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

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

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.