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. 19, 2025

Filed:

Jan. 30, 2023
Applicant:

Salesforce, Inc., San Francisco, CA (US);

Inventors:

Manli Shu, Greenbelt, MD (US);

Le Xue, Mountain View, CA (US);

Ning Yu, Palo Alto, CA (US);

Roberto Martín-Martín, Austin, TX (US);

Juan Carlos Niebles Duque, Mountain View, CA (US);

Caiming Xiong, Menlo Park, CA (US);

Ran Xu, Mountain View, CA (US);

Assignee:

Salesforce, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/64 (2022.01); G06T 3/4007 (2024.01); G06V 10/46 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 20/64 (2022.01); G06T 3/4007 (2013.01); G06V 10/46 (2022.01); G06V 10/82 (2022.01);
Abstract

Embodiments described herein provide a system for three-dimensional (3D) object detection. The system includes an input interface configured to obtain 3D point data describing spatial information of a plurality of points, and a memory storing a neural network based 3D object detection model having an encoder and a decoder. The system also includes processors to perform operations including: encoding, by the encoder, a first set of coordinates into a first set of point features and a set of object features; sampling a second set of point features from the first set of point features; generating, by attention layers at the decoder, a set of attention weights by applying cross-attention over at least the set of object features and the second set of point feature, and generate, by the decoder, a predicted bounding box among the plurality of points based on at least in part on the set of attention weights.


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