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:
Nov. 05, 2019

Filed:

Dec. 31, 2018
Applicant:

Didi Research America, Llc, Mountain View, CA (US);

Inventors:

Ruxiao Bao, Mountain View, CA (US);

Xun Xu, Mountain View, CA (US);

Assignee:

DiDi Research America, LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01); G06K 9/72 (2006.01); G06T 9/00 (2006.01); G06T 7/10 (2017.01); G06N 3/08 (2006.01); G06T 7/168 (2017.01);
U.S. Cl.
CPC ...
G06K 9/6232 (2013.01); G06K 9/6257 (2013.01); G06K 9/726 (2013.01); G06N 3/08 (2013.01); G06T 7/10 (2017.01); G06T 9/002 (2013.01); G06K 2209/21 (2013.01); G06K 2209/27 (2013.01); G06T 7/168 (2017.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

Methods and systems involving convolutional neural networks as applicable for semantic segmentation, including multi-task convolutional networks employing curriculum based transfer learning, are disclosed herein. In one example embodiment, a method of semantic segmentation involving a convolutional neural network includes training and applying the convolutional neural network. The training of the convolutional neural network includes each of training a semantic segmentation decoder network of the convolutional neural network, generating first feature maps by way of an encoder network of the convolutional neural network, based at least in part upon a dataset received at the encoder network, and training an instance segmentation decoder network of the convolutional neural network based at least in part upon the first feature maps. The applying includes receiving an image, and generating each of a semantic segmentation map and an instance segmentation map in response to the receiving of the image, in a single feedforward pass.


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