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:
Aug. 08, 2023

Filed:

Aug. 19, 2021
Applicant:

Waymo Llc, Mountain View, CA (US);

Inventors:

Zhaoyin Jia, Sunnyvale, CA (US);

Ury Zhilinsky, Foster City, CA (US);

Yun Jiang, Sunnyvale, CA (US);

Yimeng Zhang, San Jose, CA (US);

Assignee:

Waymo LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06N 3/084 (2023.01); G06V 20/58 (2022.01); G06V 10/44 (2022.01); G06V 40/10 (2022.01); G06F 18/25 (2023.01); G06N 3/045 (2023.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06N 3/00 (2023.01);
U.S. Cl.
CPC ...
G06N 3/084 (2013.01); G06F 18/25 (2023.01); G06N 3/00 (2013.01); G06N 3/045 (2023.01); G06V 10/454 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/58 (2022.01); G06V 40/103 (2022.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object detection predictions from a neural network. In some implementations, an input characterizing a first region of an environment is obtained. The input includes a projected laser image generated from a three-dimensional laser sensor reading of the first region, a camera image patch generated from a camera image of the first region, and a feature vector of features characterizing the first region. The input is processed using a high precision object detection neural network to generate a respective object score for each object category in a first set of one or more object categories. Each object score represents a respective likelihood that an object belonging to the object category is located in the first region of the environment.


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