US 12,003,734 B2
Machine learning based flow determination for video coding
Ankitesh Kumar Singh, San Diego, CA (US); Hilmi Enes Egilmez, San Diego, CA (US); Muhammed Zeyd Coban, Carlsbad, 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 Feb. 21, 2022, as Appl. No. 17/676,510.
Claims priority of provisional application 63/153,475, filed on Feb. 25, 2021.
Prior Publication US 2022/0272355 A1, Aug. 25, 2022
Int. Cl. H04N 19/139 (2014.01); H04N 5/232 (2006.01); H04N 19/172 (2014.01); H04N 19/186 (2014.01); H04N 23/63 (2023.01)
CPC H04N 19/139 (2014.11) [H04N 19/172 (2014.11); H04N 19/186 (2014.11); H04N 23/632 (2023.01)] 30 Claims
OG exemplary drawing
 
1. A method of processing video data, the method comprising:
obtaining, by a machine learning system, a latent representation of at least one luminance component for a current frame, the latent representation of the at least one luminance component of the current frame being based on the at least one luminance component of the current frame and at least one reconstructed luma component of a previous frame;
determining, by the machine learning system, motion information for the at least one luminance component of the current frame using the latent representation of the at least one luminance component of the current frame; and
determining, using the machine learning system, motion information for one or more chrominance components of the current frame using the motion information determined for the at least one luminance component for the current frame.