公开(公告)号：US20240095880A1

公开(公告)日：2024-03-21

申请号：US17948138

申请日：2022-09-19

Applicant: NVIDIA Corporation

Inventor： Shiqiu Liu ,  Jussi Rasanen ,  Michael Ranzinger ,  Guilin Liu ,  Andrew Tao ,  Bryan Christopher Catanzaro

IPC: G06T3/40 ,  G06T5/00 ,  G06T5/50

CPC classification number: G06T3/4046 ,  G06T5/002 ,  G06T5/50 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20212

Abstract: Apparatuses, systems, and techniques to use one or more neural networks to generate an upsampled version of one or more images based, at least in part, on a denoised version of said one or more images. At least one embodiment pertains to generating an upsampled high-resolution image from a noisy version and denoised version of a low-resolution image. At least one embodiment pertains to separating components of a low-resolution image before denoising an image.

公开(公告)号：US20250111661A1

公开(公告)日：2025-04-03

申请号：US18882629

申请日：2024-09-11

Applicant: NVIDIA Corporation

Inventor： Ali Hatamizadeh ,  Michael Ranzinger ,  Jan Kautz

IPC: G06V10/82 ,  G06V10/26 ,  G06V10/774 ,  G06V10/776 ,  G06V10/94

Abstract: Transformers are neural networks that learn context and thus meaning by tracking relationships in sequential data. The main building block of transformers is self-attention which allows for cross interaction among all input sequence tokens with each other. This scheme effectively captures short-and long-range spatial dependencies and imposes time and space quadratic complexity in terms of the input sequence length, which enables their use with Natural Language Processing (NLP) and computer vision tasks. While the training parallelism of transformers allows for competitive performance, unfortunately the inference is slow and expensive due to the computational complexity. The present disclosure provides a computer vision retention model that is configured for both parallel training and recurrent inference, which can enable competitive performance during training and fast and memory-efficient inferences during deployment.

公开(公告)号：US20230196662A1

公开(公告)日：2023-06-22

申请号：US17556885

申请日：2021-12-20

Applicant: Nvidia Corporation

Inventor： Pietari Kaskela ,  Andrew Tao ,  Michael Ranzinger ,  David Tarjan ,  Jonathan Filip Gustav Granskog ,  Jorge Albericio Latorre

IPC: G06T15/50 ,  G06N3/04 ,  G06T3/40 ,  G06T3/00

CPC classification number: G06T15/503 ,  G06N3/0454 ,  G06T3/4046 ,  G06T3/0093

Abstract: Apparatuses, systems, and techniques are presented to reconstruct one or more images. In at least one embodiment, one or more circuits are to use one or more neural networks to adjust one or more pixel blending weights.