Isolated Diffusion: Optimizing Multi-Concept Text-to-Image Generation Training-Freely with Isolated Diffusion Guidance

arXiv:2403.16954v1 Announce Type: new
Abstract: Large-scale text-to-image diffusion models have achieved great success in synthesizing high-quality and diverse images given target text prompts. Despite the revolutionary image generation ability, current state-of-the-art models still struggle to deal with multi-concept generation accurately in many cases. This phenomenon is known as ``concept bleeding" and displays as the unexpected overlapping or merging of various concepts. This paper presents a general approach for text-to-image diffusion models to address the mutual interference between different subjects and …

abstract art arxiv cases concept cs.cv current deal diffusion diffusion models diverse guidance image image diffusion image generation images prompts quality scale state state-of-the-art models struggle success text text-to-image training type