Video Generation Motion Control Using Bounding Box Tokens
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Solution Overview
Problem
Existing video generation models struggle to accurately understand and implement user-defined motion requirements for objects in generated videos, particularly when precise descriptions are difficult to articulate, leading to mismatches between user expectations and generated content.
Innovation Solution
A method and apparatus that utilize bounding boxes to constrain object positions and sizes, generating control tokens to guide the video generation process, ensuring that objects move according to user-defined motion modes by integrating a motion control module into the video generation model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If text descriptions are used to guide video generation, then the model can generate video content based on natural language, but the model struggles to accurately understand and implement user-defined motion requirements
Solution Approach 1:
The patent segments the control signal into two distinct types: visual tokens for content generation and control tokens for motion constraint. This segmentation allows the model to separately process content requirements and motion requirements, improving motion control accuracy while maintaining versatility.
Solution Approach 2:
The patent introduces control tokens as an intermediary element between the text description and the final video generation. These control tokens serve as a mediator that carries motion constraint information, enabling the model to accurately implement user-defined motion requirements while generating video content.
2Productivity
If machine learning models are used for motion control, then the model can generate video content, but the generated video fails to match user expectations for precise motion
Solution Approach 1:
The patent implements a feedback mechanism where the control tokens are generated from bounding box information and fed back into the video generation process. This feedback loop ensures that the generated video consistently meets the motion requirements specified by the user, improving reliability while maintaining efficiency.
Solution Approach 2:
The patent changes the parameter representation by introducing control tokens that encode motion constraints. This parameter change enables the model to reliably fulfill motion requirements while maintaining efficient video generation, as the control tokens provide direct guidance on object positioning and motion.
3Manufacturing precision
If bounding boxes are used to constrain object positions, then motion control precision is improved, but the system complexity increases
Solution Approach 1:
The patent makes the control token generation system universal by using the same bounding box processing mechanism for both single-object and multi-object scenarios. This multi-functionality reduces system complexity while maintaining high precision in object position control, as the same framework handles various control requirements.
Solution Approach 2:
The patent merges the bounding box processing and control token generation into a unified process. By combining these functions, the system achieves precise object position control without proportionally increasing complexity, as the merged process leverages existing computational resources efficiently.
Data Source
AI summary
The present disclosure relates to a method and apparatus for generating a video, an electronic device, and a computer program product. The method includes obtaining a visual token for generating an image frame in the video. The method further includes obtaining a control token for constraining position information of an object in the image frame. In addition, the method also includes generating the image frame in the video based on the visual token and the control token, where the object in the image frame satisfies the position information.