Style-based Image Generation via Staged Embedding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional machine learning models struggle to consistently apply styles to synthetic images without modifying the intended structure, often overwhelming content guidance and failing to depict intended content.
Innovation Solution
An image generation system that uses style information as guidance in later steps of the image generation process, ensuring consistent style application without altering the intended content or structure of the synthetic image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If style information is used in each step of the image generation process, then style consistency is improved, but the intended content and structure are overwhelmed and modified
Solution Approach 1:
The image generation process is divided into two distinct stages: a content generation stage where only content information is provided as guidance, and a style application stage where style information is applied to the generated content. This segmentation allows style and content to be processed separately without interference, resolving the contradiction between style consistency and content preservation.
Solution Approach 2:
The content generation step is performed first as a preliminary action, creating the base image with intended content and structure before style information is applied in the second step. This ensures that the content structure is established before style influences could potentially modify it, preserving the intended information while still achieving style consistency.
2Manufacturing precision
If style information is applied strongly to ensure consistent style appearance, then style accuracy is improved, but the intended content structure is modified
Solution Approach 1:
By separating the generation process into content generation and style application stages, the system can apply strong style transformations in the second stage without affecting the content structure that was established in the first stage. This segmentation protects the content structure from style-induced modifications while maintaining high style accuracy.
Solution Approach 2:
The intermediate representation created after the content generation step serves as a mediator between content information and style information. This intermediate state allows style information to be applied to a stable content structure without directly modifying the original content guidance, thus preserving the intended shape and structure while achieving accurate style application.
3Productivity
If conventional image generation models are used to generate stylized images, then content generation is achieved, but style application is inconsistent and content is overwhelmed
Solution Approach 1:
The system segments the image generation task into two independent sub-tasks: content generation and style application. This segmentation improves reliability by ensuring that style information is applied consistently in a dedicated second step after content is generated, rather than competing for influence throughout the entire generation process as in conventional models.
Solution Approach 2:
By performing content generation as a preliminary action before style application, the system establishes a stable content foundation that can then be reliably stylized. This preliminary content generation ensures that the base image accurately reflects the intended content structure before style transformations are applied, improving overall reliability of the stylized output.
Data Source
AI summary
A method, apparatus, non-transitory computer readable medium, and system for media processing includes obtaining a text prompt and a style input, where the text prompt describes image content and the style input describes an image style, generating a text embedding based on the text prompt, where the text embedding represents the image content, generating a style embedding based on the style input, where the style embedding represents the image style, and generating a synthetic image based on the text embedding and the style embedding, where the text embedding is provided to the image generation model at a first step and the style embedding is provided to the image generation model at a second step after the first step.