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:
Jun. 07, 2022

Filed:

Apr. 13, 2020
Applicant:

Adobe Inc., San Jose, CA (US);

Inventors:

Federico Perazzi, San Francisco, CA (US);

Zhe Lin, Fremont, CA (US);

Ping Hu, Boston, MA (US);

Oliver Wang, Seattle, WA (US);

Fabian David Caba Heilbron, San Jose, CA (US);

Assignee:

Adobe Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/40 (2022.01); G06N 3/04 (2006.01); G06T 7/11 (2017.01); G06F 17/15 (2006.01);
U.S. Cl.
CPC ...
G06V 20/49 (2022.01); G06F 17/15 (2013.01); G06N 3/0454 (2013.01); G06T 7/11 (2017.01); G06T 2207/10016 (2013.01); G06T 2207/20084 (2013.01);
Abstract

A Video Semantic Segmentation System (VSSS) is disclosed that performs accurate and fast semantic segmentation of videos using a set of temporally distributed neural networks. The VSSS receives as input a video signal comprising a contiguous sequence of temporally-related video frames. The VSSS extracts features from the video frames in the contiguous sequence and based upon the extracted features, selects, from a set of labels, a label to be associated with each pixel of each video frame in the video signal. In certain embodiments, a set of multiple neural networks are used to extract the features to be used for video segmentation and the extraction of features is distributed among the multiple neural networks in the set. A strong feature representation representing the entirety of the features is produced for each video frame in the sequence of video frames by aggregating the output features extracted by the multiple neural networks.


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