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:
May. 19, 2026

Filed:

Apr. 27, 2023
Applicant:

Toyota Research Institute, Inc., Los Altos, CA (US);

Inventors:

Dian Chen, Mountain View, CA (US);

Rares A. Ambrus, San Francisco, CA (US);

Jie Li, Los Altos, CA (US);

Adrien David Gaidon, Mountain View, CA (US);

Vitor Campagnolo Guizilini, Santa Clara, CA (US);

Assignees:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/64 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 10/94 (2022.01);
U.S. Cl.
CPC ...
G06V 20/64 (2022.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 10/95 (2022.01);
Abstract

Systems and methods for training multi-view 3D object detection frameworks are disclosed herein. In one example, a method includes the steps of predicting one or more predicted bounding boxes representing one or more objects within multi-view images using a decoder that considers (a) feature embeddings generated from image features from multi-view images, (b) geometric positional encodings that are associated with the feature embeddings, and (c) view-dependent queries, determining a viewpoint equivariance loss based on a comparison of the one or more predicted bounding boxes with one or more ground truth bounding boxes, and adjusting model weights of networks forming the multi-view 3D object detection framework based on the viewpoint equivariance loss.


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