Artificial intelligence-based video processing method and device, equipment and storage medium

CN123035322APending Publication Date: 2026-11-03BEIJING BAIDU NETCOM SCI & TECH CO LTD
View PDF 0 Cites 0 Cited by

Patent Information

Application Number
CN202611248249.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-08-17
Publication Date
2026-11-03

AI Technical Summary

Technical Problem

Existing edge-cloud collaborative video processing solutions suffer from frame extraction redundancy and long processing times. This wastes network bandwidth and computing power, especially in simple videos, while key shots may be missed in complex videos.

Method used

By selecting frames to be processed for each shot of the target video and performing quality assessments on the server, the system achieves frame extraction and transmission simultaneously. A neural network model is used for target task processing, and frames are dynamically replaced based on the quality assessment results to ensure that the frame quality meets the requirements.

Benefits of technology

It improves the efficiency and accuracy of video processing, reduces the transmission of invalid frames, ensures the integrity and processing quality of key shots, and enhances the execution performance of neural network models.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN123035322A_ABST
    Figure CN123035322A_ABST
Patent Text Reader

Abstract

The present disclosure provides an artificial intelligence-based video processing method and device, equipment and storage medium, relating to the technical field of computers, and in particular to the technical field of video processing, large models, artificial intelligence and the like. The specific implementation scheme is: from the target video, for each shot, a to-be-processed frame is selected; the to-be-processed frame of each shot is sent to the server, so that the server performs quality evaluation on the received to-be-processed frame; in response to the replacement frame requirement sent by the server for the target frame, the replacement frame of the target frame is reselected and sent to the server; the server is used to execute a target task for the target video based on a neural network model; the target frame is a to-be-processed frame whose quality evaluation result does not satisfy a first quality requirement.
Need to check novelty before this filing date? Find Prior Art