Adjustable Complexity Image Generation via Layered Style Embedding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image generation models, such as diffusion-based models, tend to produce overly detailed and realistic images, which can complicate the conversion of images to vector format, as they lack control over complexity, making them unsuitable for tasks requiring simpler designs or vectorization.
Innovation Solution
An image generation model incorporating a diffusion prior model that generates a style embedding encoding visual characteristics like flat colors and simple shapes, allowing for adjustable complexity by selectively applying the style embedding to various layers of the diffusion model during image synthesis, enabling the production of images with controllable complexity levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If diffusion-based models are used to generate realistic images, then image realism is improved, but image complexity increases making vectorization difficult
Solution Approach 1:
The patent applies dynamics by making the style embedding application dynamic and adjustable. The style embedding can be selectively applied to different layers of the diffusion model with varying strengths, allowing the system to adapt between generating highly realistic images and simplified vector-friendly images based on user needs. This dynamic control resolves the contradiction by enabling the same model to produce outputs across the complexity spectrum.
Solution Approach 2:
The patent changes parameters by introducing a style embedding with adjustable application strength and layer selection. By modifying which layers receive the style embedding and at what intensity, the system can transform the output from highly detailed realistic images to simplified vector-friendly images, thus resolving the contradiction between realism and complexity.
2Ease of operation
If style embedding is applied to more layers, then complexity control is improved, but computational cost increases
Solution Approach 1:
The patent applies partial action by allowing selective application of style embedding to only certain layers of the diffusion model rather than all layers. Users can choose to apply the style embedding to fewer layers when computational resources are limited, or to more layers when greater complexity control is needed, thus balancing ease of operation with computational cost.
Solution Approach 2:
The system dynamically adjusts the number of layers receiving style embedding based on user input and computational constraints. This dynamic configuration allows the system to optimize between complexity control capability and computational resource consumption, resolving the contradiction between ease of operation and energy use.
Data Source
AI summary
A method, apparatus, non-transitory computer readable medium, and system for generating images with an adjustable level of complexity includes obtaining a content prompt, a style prompt, and a complexity value. The content prompt describes an image element, the style prompt indicates an image style, and the complexity value indicates a level of influence of the style prompt. Embodiments then generate, using an image generation model, an output image based on the content prompt, the style prompt, and the complexity value, wherein the output image includes the image element with a level of the image style based on the complexity value.