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.
Patent No.:
Date of Patent:
Dec. 13, 2022
Filed:
Aug. 17, 2017
Applicant:
Magic Pony Technology Limited, London, GB;
Inventors:
Zehan Wang, London, GB;
Robert David Bishop, London, GB;
Wenzhe Shi, London, GB;
Jose Caballero, London, GB;
Andrew Peter Aitken, London, GB;
Johannes Totz, London, GB;
Assignee:
Twitter, Inc., San Francisco, CA (US);
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 19/36 (2014.01); G06T 3/40 (2006.01); H04N 19/80 (2014.01); H04N 19/86 (2014.01); H04N 19/59 (2014.01); G06T 5/00 (2006.01); H04N 19/117 (2014.01); H04N 19/177 (2014.01); H04N 19/46 (2014.01); H04N 19/142 (2014.01); H04N 19/154 (2014.01); G06V 10/40 (2022.01); G06V 30/194 (2022.01); H04N 19/31 (2014.01); H04N 19/33 (2014.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); H04N 7/01 (2006.01); G06T 7/11 (2017.01); G06K 9/62 (2022.01); H04N 19/172 (2014.01); H04N 19/87 (2014.01); H04N 19/176 (2014.01);
U.S. Cl.
CPC ...
H04N 19/36 (2014.11); G06K 9/6215 (2013.01); G06N 3/04 (2013.01); G06N 3/049 (2013.01); G06N 3/0445 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06T 3/40 (2013.01); G06T 3/4007 (2013.01); G06T 3/4046 (2013.01); G06T 3/4053 (2013.01); G06T 5/001 (2013.01); G06T 5/002 (2013.01); G06T 7/11 (2017.01); G06V 10/40 (2022.01); G06V 30/194 (2022.01); H04N 7/0117 (2013.01); H04N 19/117 (2014.11); H04N 19/142 (2014.11); H04N 19/154 (2014.11); H04N 19/172 (2014.11); H04N 19/177 (2014.11); H04N 19/31 (2014.11); H04N 19/33 (2014.11); H04N 19/46 (2014.11); H04N 19/59 (2014.11); H04N 19/80 (2014.11); H04N 19/86 (2014.11); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); H04N 19/176 (2014.11); H04N 19/87 (2014.11);
Abstract
A method for developing an enhancement model for low-quality visual data, the method comprising the steps of receiving one or more sections of higher-quality visual data; and training a hierarchical algorithm. The hierarchical algorithm is operable to increase the quality of one or more sections of lower-quality visual data so as to substantially reproduce the one or more sections of higher-quality visual data. The hierarchical algorithm is then outputted.