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:
Jul. 01, 2025

Filed:

Nov. 14, 2022
Applicant:

Beijing Baidu Netcom Science Technology Co., Ltd., Beijing, CN;

Inventors:

Jian Wang, Beijing, CN;

Xiangbo Su, Beijing, CN;

Qiman Wu, Beijing, CN;

Zhigang Wang, Beijing, CN;

Hao Sun, Beijing, CN;

Errui Ding, Beijing, CN;

Jingdong Wang, Beijing, CN;

Tian Wu, Beijing, CN;

Haifeng Wang, Beijing, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 18/00 (2023.01); G06F 18/25 (2023.01); G06N 3/045 (2023.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06V 10/40 (2022.01); G06V 10/77 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/40 (2022.01); G06V 30/19 (2022.01);
U.S. Cl.
CPC ...
G06F 18/00 (2023.01); G06F 18/25 (2023.01); G06N 3/045 (2023.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06V 10/40 (2022.01); G06V 10/7715 (2022.01); G06V 10/80 (2022.01); G06V 10/806 (2022.01); G06V 10/82 (2022.01); G06V 20/46 (2022.01); G06V 30/1918 (2022.01);
Abstract

Provided are a joint perception model training method, a joint perception method, a device, and a storage medium. The joint perception model training method includes: acquiring sample images and perception tags of the sample images; acquiring a preset joint perception model, where the joint perception model includes a feature extraction network and a joint perception network; performing feature extraction on the sample images through the feature extraction network to obtain target sample features; performing joint perception through the joint perception network according to the target sample features to obtain perception prediction results; and training the preset joint perception model according to the perception prediction results and the perception tags, where the joint perception includes executing at least two perception tasks.


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