US 12,075,053 B2
Image compression and decoding, video compression and decoding: methods and systems
Chri Besenbruch, London (GB); Ciro Cursio, London (GB); Christopher Finlay, London (GB); Vira Koshkina, London (GB); Alexander Lytchier, London (GB); Jan Xu, London (GB); and Arsalan Zafar, London (GB)
Assigned to DEEP RENDER LTD., London (GB)
Filed by DEEP RENDER LTD, London (GB)
Filed on Aug. 4, 2023, as Appl. No. 18/230,376.
Application 18/230,376 is a continuation of application No. 18/055,666, filed on Nov. 15, 2022.
Application 18/055,666 is a continuation of application No. 17/740,716, filed on May 10, 2022, granted, now 11,677,948.
Application 17/740,716 is a continuation of application No. PCT/GB2021/051041, filed on Apr. 29, 2021.
Claims priority of provisional application 63/053,807, filed on Jul. 20, 2020.
Claims priority of provisional application 63/017,295, filed on Apr. 29, 2020.
Claims priority of application No. 2006275 (GB), filed on Apr. 29, 2020; application No. 2008241 (GB), filed on Jun. 2, 2020; application No. 2011176 (GB), filed on Jul. 20, 2020; application No. 2012461 (GB), filed on Aug. 11, 2020; application No. 2012462 (GB), filed on Aug. 11, 2020; application No. 2012463 (GB), filed on Aug. 11, 2020; application No. 2012465 (GB), filed on Aug. 11, 2020; application No. 2012467 (GB), filed on Aug. 11, 2020; application No. 2012468 (GB), filed on Aug. 11, 2020; application No. 2012469 (GB), filed on Aug. 11, 2020; application No. 2016824 (GB), filed on Oct. 23, 2020; and application No. 2019531 (GB), filed on Dec. 10, 2020.
Prior Publication US 2023/0388503 A1, Nov. 30, 2023
Int. Cl. H04N 19/126 (2014.01); G06N 3/045 (2023.01); G06N 3/084 (2023.01); G06T 3/4046 (2024.01); G06T 9/00 (2006.01); G06V 10/774 (2022.01); H04N 19/13 (2014.01)
CPC H04N 19/126 (2014.11) [G06N 3/045 (2023.01); G06N 3/084 (2013.01); G06T 3/4046 (2013.01); G06T 9/002 (2013.01); G06V 10/774 (2022.01); H04N 19/13 (2014.11)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for lossy image or video compression, transmission and decoding, the method including the steps of:
(i) receiving a first input image and a second input image at a first computer system;
(ii) encoding the first input image and the second input image using a first trained neural network, using the first computer system, to produce a latent representation;
(iii) quantizing the latent representation using the first computer system to produce a quantized latent;
(iv) entropy encoding the quantized latent into a bitstream, using the first computer system;
(v) transmitting the bitstream to a second computer system;
(vi) the second computer system entropy decoding the bitstream to produce the quantized latent;
(vii) the second computer system using a second trained neural network to produce an output image from the quantized latent, wherein the output image is an approximation of the input image;
wherein one or more of steps (i)-(vii) comprise the use of an iterative solving method, and
wherein in step (vi), producing the quantized latent comprises, by the second computer system, processing at least part of the entropy decoded bitstream by applying an iterative solving method to said at least part of the entropy decoded bitstream, said at least part of the entropy decoded bitstream comprising spatial and temporal information associated with the first input image and the second input image.