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:
Dec. 03, 2019

Filed:

Dec. 22, 2017
Applicant:

Facebook, Inc., Menlo Park, CA (US);

Inventors:

Pedro Henrique Oliveira Pinheiro, Saint Sulpice, CH;

Ronan Stéfan Collobert, Mountain View, CA (US);

Piotr Dollar, San Mateo, CA (US);

Assignee:

Facebook, Inc., Menlo Park, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06K 9/68 (2006.01); G06N 20/00 (2019.01); G06F 15/76 (2006.01); G06K 9/00 (2006.01); G06K 9/46 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6212 (2013.01); G06F 15/76 (2013.01); G06K 9/00677 (2013.01); G06K 9/4628 (2013.01); G06K 9/6256 (2013.01); G06K 9/6274 (2013.01); G06K 9/6857 (2013.01); G06N 3/04 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06K 9/00335 (2013.01);
Abstract

In one embodiment a plurality of patches of an image are processed, using a first set of layers of a convolutional neural network, to output a plurality of object proposals associated with the plurality of patches of the image. Each patch includes one or more pixels of the image. Each object proposal includes a prediction as to a location of an object in the respective patch. Using a second set of layers of the convolutional neural network, the plurality of object proposals outputted by the first set of layers are processed to generate a plurality of refined object proposals. Each refined object proposal includes pixel-level information for the respective patch of the image. The first layer in the second set of layers of the convolutional neural network takes as input the plurality of object proposals outputted by the first set of layers. Each layer after the first layer in the second set of layers takes as input the output of a preceding layer in the second set of layers combined with the output of a respective layer of the first set of layers.


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