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.

Date of Patent:
Jan. 16, 2024

Filed:

Mar. 11, 2021
Applicant:

Beihang University, Beijing, CN;

Inventors:

Bin Zhou, Beijing, CN;

Zongdai Liu, Beijing, CN;

Qinping Zhao, Beijing, CN;

Hongyu Wu, Beijing, CN;

Assignee:

BEIHANG UNIVERSITY, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/22 (2022.01); G06T 7/73 (2017.01); B60W 30/09 (2012.01); G06T 19/00 (2011.01); G06V 20/56 (2022.01); G06V 20/64 (2022.01); G06F 18/214 (2023.01); G06F 18/2134 (2023.01); G06V 10/44 (2022.01);
U.S. Cl.
CPC ...
G06V 10/22 (2022.01); B60W 30/09 (2013.01); G06F 18/214 (2023.01); G06F 18/21343 (2023.01); G06T 7/73 (2017.01); G06T 19/006 (2013.01); G06V 10/454 (2022.01); G06V 20/56 (2022.01); G06V 20/653 (2022.01); B60W 2420/42 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30261 (2013.01); G06T 2219/2004 (2013.01);
Abstract

The present disclosure provides a visual perception method and apparatus, a perception network training method and apparatus, a device and a storage medium. The visual perception method recognizes the acquired image to be perceived with a perception network to determine a perceived target and a pose of the perceived target, and finally determines a control command according to a preset control algorithm and the pose, so as to enable an object to be controlled to determine a processing strategy for the perceived target according to the control command. According to the perception network training method, acquire image data and model data, then generate an edited image with a preset editing algorithm according to a 2D image and a 3D model, and finally train the perception network to be trained according to the edited image and the label.


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