Generative Model Image Partial Area Generation
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Solution Overview
Problem
Existing image processing technologies struggle to maintain user satisfaction when objects in an image are resized or repositioned, as the objects often fail to match the surrounding environment, leading to decreased satisfaction.
Innovation Solution
A method using a generative model to generate a partial area of an image, involving the use of a first generative model to create an intermediate generated image and a second generative model to produce a final generated image, ensuring the image information is consistent and aesthetically pleasing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If objects are resized or repositioned in an image using existing image processing technology, then the position or size of objects can be changed, but the objects do not match the surroundings in the image, leading to decreased user satisfaction
Solution Approach 1:
The patent divides the image processing task into multiple stages using different generative models. The first generative model processes the original image to create an intermediate result, while the second generative model refines this result to generate the final output. This segmentation allows each model to specialize in specific aspects of image generation, improving both the ability to modify objects and the quality of integration with surroundings.
Solution Approach 2:
The patent introduces an intermediate generated image as a mediator between the original image and the final generated image. This intermediate result serves as a bridge that captures initial transformations while allowing subsequent refinement, enabling smooth transitions and better integration of modified objects with the surrounding environment.
2Productivity
If a single generative model is used to generate image content, then the processing is simpler and faster, but the image quality and consistency are insufficient
Solution Approach 1:
The patent employs multiple generative models (first and second generative models) that process images in sequence. Each model contributes specific capabilities to the overall generation process, with the first model handling initial content creation and the second model refining details and consistency. This multi-stage approach balances processing efficiency with enhanced image quality.
Solution Approach 2:
The patent combines outputs from different generative models to create a composite final image. By integrating results from multiple models with different strengths and characteristics, the system achieves superior image quality and consistency that would be difficult to obtain with a single model, while maintaining reasonable processing speeds through efficient pipeline design.
Data Source
AI summary
Provided are a method of generating a partial area of an image by using a generative model and an electronic device for performing the method. The method of generating a partial area of an image by using a generative model includes obtaining an image comprising information of the partial area, obtaining an intermediate generated image by inputting the image into a first generative model, the intermediate generated image comprising first image information corresponding to the partial area, and obtaining a final generated image comprising second image information by inputting the image and the intermediate generated image to a second generative model, the second image information being at least partially different from the first image information.