Neural Contrast: Leveraging Generative Editing for Graphic Design Recommendations
Journal:
arXiv
Published Date:
Sep 26, 2024
Abstract
Creating visually appealing composites requires optimizing both text and
background for compatibility. Previous methods have focused on simple design
strategies, such as changing text color or adding background shapes for
contrast. These approaches are often destructive, altering text color or
partially obstructing the background image. Another method involves placing
design elements in non-salient and contrasting regions, but this isn't always
effective, especially with patterned backgrounds. To address these challenges,
we propose a generative approach using a diffusion model. This method ensures
the altered regions beneath design assets exhibit low saliency while enhancing
contrast, thereby improving the visibility of the design asset.
