Video Description Model Constraint for Accurate Copy Generation
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Solution Overview
Problem
Existing multimedia platforms rely on user-defined descriptions for video content, which often fail to accurately convey the real meaning of videos, leading to inaccuracies in copy information.
Innovation Solution
A processing method and apparatus that utilize a video description model to generate copy information based on a task prompt and copy keyword, constraining the model to improve the accuracy and relevance of the generated information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If user-defined descriptions are used for video content, then the ease of operation is improved, but the measurement precision of copy information deteriorates
Solution Approach 1:
The system enables automatic copy information generation through a video description model that processes video content autonomously without requiring user-defined descriptions. The model extracts and generates copy information directly from video data, achieving both ease of operation and measurement precision by eliminating the need for manual input while maintaining accurate representation of video content
Solution Approach 2:
The patent replaces the mechanical system of user-defined descriptions with an automated AI-based video description model. This substitution allows the system to automatically analyze video content and generate copy information, thereby improving measurement precision while maintaining ease of operation through automated processing
2Measurement precision
If automated copy information generation is implemented, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The video description model serves multiple functions including video content analysis, copy information generation, and constraint-based filtering. By consolidating these functions into a single multi-functional model, the system improves measurement precision while managing device complexity through unified processing architecture
Solution Approach 2:
The system adjusts model parameters and constraints dynamically based on the video content and task requirements. By changing parameters such as constraint strength and generation thresholds, the system achieves high measurement precision without requiring overly complex fixed architectures, thus managing device complexity through adaptive parameter tuning
Data Source
AI summary
Provided are a processing method and apparatus, an electronic device and a medium. The method includes steps described below. A target video is acquired; video information of the target video is determined; copy information corresponding to the video information is generated by using a video description model, where the copy information is generated by using the video description model and based on a task prompt and a copy keyword. Through this method, the video description model is constrained based on the task prompt and the copy keyword, so that the copy information of the target video is generated more accurately, and the coupling degree between the copy information and the target video is improved.