Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding
Researchers have developed a new framework called CCE-Diffusion to improve the quality of images generated through foreground conditioned outpainting. This method addresses artifacts caused by misalignment between text prompts and visual instances by customizing concept embeddings. The CCE-Module, a key component of the framework, bridges generic semantics with specific visual details, leading to significantly reduced artifacts and enhanced image quality. AI
IMPACT Enhances image generation quality by reducing artifacts, potentially lowering costs for product showcasing.