公开(公告)号：US10665011B1

公开(公告)日：2020-05-26

申请号：US16428482

申请日：2019-05-31

Applicant: Adobe Inc. ,  Université Laval

Inventor： Kalyan Sunkavalli ,  Sunil Hadap ,  Nathan Carr ,  Jean-Francois Lalonde ,  Mathieu Garon

IPC: G06T15/80 ,  G06N20/10 ,  G06T19/00 ,  G06N3/08 ,  G06T15/00

Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that use a local-lighting-estimation-neural network to render a virtual object in a digital scene by using a local-lighting-estimation-neural network to analyze both global and local features of the digital scene and generate location-specific-lighting parameters for a designated position within the digital scene. For example, the disclosed systems extract and combine such global and local features from a digital scene using global network layers and local network layers of the local-lighting-estimation-neural network. In certain implementations, the disclosed systems can generate location-specific-lighting parameters using a neural-network architecture that combines global and local feature vectors to spatially vary lighting for different positions within a digital scene.

公开(公告)号：US20200302684A1

公开(公告)日：2020-09-24

申请号：US16877227

申请日：2020-05-18

Applicant: ADOBE INC.

Inventor： Kalyan Sunkavalli ,  Sunil Hadap ,  Nathan Carr ,  Mathieu Garon

IPC: G06T15/50 ,  G06K9/62 ,  G06K9/00 ,  G06T19/00

Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that use a local-lighting-estimation-neural network to estimate lighting parameters for specific positions within a digital scene for augmented reality. For example, based on a request to render a virtual object in a digital scene, a system uses a local-lighting-estimation-neural network to generate location-specific-lighting parameters for a designated position within the digital scene. In certain implementations, the system also renders a modified digital scene comprising the virtual object at the designated position according to the parameters. In some embodiments, the system generates such location-specific-lighting parameters to spatially vary and adapt lighting conditions for different positions within a digital scene. As requests to render a virtual object come in real (or near real) time, the system can quickly generate different location-specific-lighting parameters that accurately reflect lighting conditions at different positions within a digital scene in response to render requests.

公开(公告)号：US11158117B2

公开(公告)日：2021-10-26

申请号：US16877227

申请日：2020-05-18

Applicant: ADOBE INC.

Inventor： Kalyan Sunkavalli ,  Sunil Hadap ,  Nathan Carr ,  Mathieu Garon

IPC: G06T15/00 ,  G06T15/50 ,  G06K9/62 ,  G06T19/00 ,  G06K9/00

Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that use a local-lighting-estimation-neural network to estimate lighting parameters for specific positions within a digital scene for augmented reality. For example, based on a request to render a virtual object in a digital scene, a system uses a local-lighting-estimation-neural network to generate location-specific-lighting parameters for a designated position within the digital scene. In certain implementations, the system also renders a modified digital scene comprising the virtual object at the designated position according to the parameters. In some embodiments, the system generates such location-specific-lighting parameters to spatially vary and adapt lighting conditions for different positions within a digital scene. As requests to render a virtual object come in real (or near real) time, the system can quickly generate different location-specific-lighting parameters that accurately reflect lighting conditions at different positions within a digital scene in response to render requests.

公开(公告)号：US10692277B1

公开(公告)日：2020-06-23

申请号：US16360901

申请日：2019-03-21

Applicant: Adobe Inc.

Inventor： Kalyan Sunkavalli ,  Sunil Hadap ,  Nathan Carr ,  Mathieu Garon

IPC: G06K9/00 ,  G06T15/50 ,  G06K9/62 ,  G06T19/00

Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that use a local-lighting-estimation-neural network to estimate lighting parameters for specific positions within a digital scene for augmented reality. For example, based on a request to render a virtual object in a digital scene, a system uses a local-lighting-estimation-neural network to generate location-specific-lighting parameters for a designated position within the digital scene. In certain implementations, the system also renders a modified digital scene comprising the virtual object at the designated position according to the parameters. In some embodiments, the system generates such location-specific-lighting parameters to spatially vary and adapt lighting conditions for different positions within a digital scene. As requests to render a virtual object come in real (or near real) time, the system can quickly generate different location-specific-lighting parameters that accurately reflect lighting conditions at different positions within a digital scene in response to render requests.