公开(公告)号：US20240303840A1

公开(公告)日：2024-09-12

申请号：US18508139

申请日：2023-11-13

Applicant: NVIDIA CORPORATION

Inventor： Chao LIU ,  Benjamin ECKART ,  Jan KAUTZ

IPC: G06T7/50 ,  G06T7/20 ,  G06V10/762

CPC classification number: G06T7/50 ,  G06T7/20 ,  G06V10/762

Abstract: The disclosed method for generating a first depth map for a first frame of a video includes performing one or more operations to generate a first intermediate depth map based on the first frame and a second frame preceding the first frame within the video, performing one or more operations to generate a second intermediate depth map based on the first frame, and performing one or more operations to combine the first intermediate depth map and the second intermediate depth map to generate the first depth map.

公开(公告)号：US20230267306A1

公开(公告)日：2023-08-24

申请号：US17933806

申请日：2022-09-20

Applicant: NVIDIA CORPORATION

Inventor： Benjamin ECKART ,  Jan KAUTZ ,  Chao LIU ,  Benjamin WU

IPC: G06N3/04 ,  G06T5/10

CPC classification number: G06N3/0454 ,  G06T5/10 ,  G06T2207/20056

Abstract: In various embodiments, a training application generates a trained machine learning model that represents items in a spectral domain. The training application executes a first neural network on a first set of data points associated with both a first item and the spectral domain to generate a second neural network. Subsequently, the training application generates a set of predicted data points that are associated with both the first item and the spectral domain via the second neural network. The training application generates the trained machine learning model based on the first neural network, the second neural network, and the set of predicted data points. The trained machine learning model maps one or more positions within the spectral domain to one or more values associated with an item based on a set of data points associated with both the item and the spectral domain.

公开(公告)号：US20230267656A1

公开(公告)日：2023-08-24

申请号：US17933813

申请日：2022-09-20

Applicant: NVIDIA CORPORATION

Inventor： Benjamin ECKART ,  Jan KAUTZ ,  Chao LIU ,  Benjamin WU

IPC: G06T11/00 ,  G06T7/00

CPC classification number: G06T11/003 ,  G06T7/0012 ,  G06T2207/20056 ,  G06T2207/20081

Abstract: In various embodiments, an inference application constructs medical images. The inference application executes a first trained machine learning model on a set of data points associated with a both a medical item and a spectral domain to generate a second model that represents the medical item within the spectral domain. The inference application maps a set of positions to a set of predicted values associated with both the medical item and the spectral domain via the second model. The inference application constructs an image of the medical item based on the first set of predicted values.

公开(公告)号：US20230267659A1

公开(公告)日：2023-08-24

申请号：US17933811

申请日：2022-09-20

Applicant: NVIDIA CORPORATION

Inventor： Benjamin ECKART ,  Jan KAUTZ ,  Chao LIU ,  Benjamin WU

IPC: G06T11/00 ,  G06F17/14 ,  G01B9/02

CPC classification number: G06T11/006 ,  G06F17/141 ,  G01B9/02041

Abstract: In various embodiments, an inference application reconstructs representations of items in a spectral domain. The inference application maps a first set of data points associated with a both an item and the spectral domain to conditioning information via a first trained machine learning model. The inference application updates a second trained machine learning model based on the conditioning information to generate a model that represents the item within the spectral domain. The inference application generates a second set of data points associated with both the item and the spectral domain via the model. The inference application constructs an image associated with the item based on the second set of data points.