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. 11, 2021

Filed:

Oct. 09, 2018
Applicant:

The Board of Trustees of the Leland Stanford Junior University, Stanford, CA (US);

Inventors:

Lyne P. Tchapmi, Stanford, CA (US);

Christopher B. Choy, Stanford, CA (US);

Iro Armeni, Stanford, CA (US);

JunYoung Gwak, Stanford, CA (US);

Silvio Savarese, Stanford, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/10 (2017.01); G06T 1/20 (2006.01); G06N 5/04 (2006.01); G06T 3/40 (2006.01); G06N 3/08 (2006.01); G06K 9/00 (2006.01); G06T 7/11 (2017.01); G06T 7/143 (2017.01);
U.S. Cl.
CPC ...
G06T 7/10 (2017.01); G06K 9/00 (2013.01); G06N 3/084 (2013.01); G06N 5/04 (2013.01); G06T 1/20 (2013.01); G06T 3/4007 (2013.01); G06T 7/11 (2017.01); G06T 7/143 (2017.01); G06T 2207/10028 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

Systems and methods for obtaining 3D point-level segmentation of 3D point clouds in accordance with various embodiments of the invention are disclosed. One embodiment includes: at least one processor, and a memory containing a segmentation pipeline application. In addition, the segmentation pipeline application configures the at least one processor to: pre-process a 3D point cloud to group 3D points; provide the groups of 3D points to a 3D neural network to generate initial label predictions for the groups of 3D points; interpolate label predictions for individual 3D points based upon initial label predictions for at least two neighboring groups of 3D points including the group of 3D points to which a given individual 3D point belongs; refine the label predictions using a graph neural network; and output a segmented 3D point cloud.


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