The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Dec. 10, 2024
Filed:
Jul. 15, 2021
Nvidia Corporation, Santa Clara, CA (US);
Nikolai Smolyanskiy, Seattle, WA (US);
Ryan Oldja, Redmond, WA (US);
Ke Chen, Sunnyvale, CA (US);
Alexander Popov, Kirkland, WA (US);
Joachim Pehserl, Lynnwood, WA (US);
Ibrahim Eden, Redmond, WA (US);
Tilman Wekel, Sunnyvale, CA (US);
David Wehr, Redmond, WA (US);
Ruchi Bhargava, Redmond, WA (US);
David Nister, Bellevue, WA (US);
NVIDIA Corporation, Santa Clara, CA (US);
Abstract
A deep neural network(s) (DNN) may be used to detect objects from sensor data of a three dimensional (3D) environment. For example, a multi-view perception DNN may include multiple constituent DNNs or stages chained together that sequentially process different views of the 3D environment. An example DNN may include a first stage that performs class segmentation in a first view (e.g., perspective view) and a second stage that performs class segmentation and/or regresses instance geometry in a second view (e.g., top-down). The DNN outputs may be processed to generate 2D and/or 3D bounding boxes and class labels for detected objects in the 3D environment. As such, the techniques described herein may be used to detect and classify animate objects and/or parts of an environment, and these detections and classifications may be provided to an autonomous vehicle drive stack to enable safe planning and control of the autonomous vehicle.