US 11,967,151 B2
Video classification method and apparatus, model training method and apparatus, device, and storage medium
Yan Li, Shenzhen (CN); Xintian Shi, Shenzhen (CN); and Bin Ji, Shenzhen (CN)
Assigned to TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED, Shenzhen (CN)
Filed by Tencent Technology (Shenzhen) Company Limited, Shenzhen (CN)
Filed on Oct. 29, 2021, as Appl. No. 17/515,164.
Application 17/515,164 is a continuation of application No. PCT/CN2020/117358, filed on Sep. 24, 2020.
Claims priority of application No. 201911121362.5 (CN), filed on Nov. 15, 2019.
Prior Publication US 2022/0051025 A1, Feb. 17, 2022
Int. Cl. G06K 9/00 (2022.01); G06F 18/214 (2023.01); G06F 18/25 (2023.01); G06V 20/40 (2022.01)
CPC G06V 20/41 (2022.01) [G06F 18/214 (2023.01); G06F 18/253 (2023.01); G06V 20/46 (2022.01); G06V 20/49 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A video classification method performed by a computer device, the method comprising:
obtaining a video;
dividing the video into n segments of equal length, n being a positive integer;
selecting n image frames from the video, each image frame from a corresponding one of the n segments;
extracting respective feature information of each of the n image frames by using a feature extraction network;
fusing the feature information of each of the n image frames according to a learned feature fusion policy, the learned feature fusion policy being used for indicating, when a first image frame in the n image frames is fused with feature information of other image frames in the n image frames, proportions of the feature information of the other image frames; and
determining a classification result of the video according to the respective feature information of the n image frames, wherein feature information of an edge image frame in the n image frames is weighted differently from feature information of a non-edge image frame in the n image frames.