US 12,327,384 B2
Multiple neural network models for filtering during video coding
Hongtao Wang, San Diego, CA (US); Venkata Meher Satchit Anand Kotra, Munich (DE); Jianle Chen, San Diego, CA (US); and Marta Karczewicz, San Diego, CA (US)
Assigned to QUALCOMM Incorporated, San Diego, CA (US)
Filed by QUALCOMM Incorporated, San Diego, CA (US)
Filed on Dec. 30, 2021, as Appl. No. 17/566,282.
Claims priority of provisional application 63/133,733, filed on Jan. 4, 2021.
Prior Publication US 2022/0215593 A1, Jul. 7, 2022
Int. Cl. H04N 19/11 (2014.01); G06T 9/00 (2006.01); H04N 19/61 (2014.01); H04N 19/90 (2014.01)
CPC G06T 9/002 (2013.01) [H04N 19/11 (2014.11); H04N 19/619 (2014.11); H04N 19/90 (2014.11)] 32 Claims
OG exemplary drawing
 
1. A method of filtering decoded video data, the method comprising:
receiving, by a neural network filtering unit of a video decoding device, data for a decoded picture of video data;
receiving, by the neural network filtering unit, data from one or more other units of the video decoding device, the data from the one or more other units being different than the data for the decoded picture, and wherein receiving the data from the one or more other units of the video decoding device comprises receiving boundary strength data from a deblocking unit of the video decoding device;
determining, by the neural network filtering unit, one or more neural network models to be used to filter a portion of the decoded picture; and
filtering, by the neural network filtering unit, the portion of the decoded picture using the one or more neural network models and the data from the one or more other units of the video decoding device, including the boundary strength data.