Obtaining Favorable Layouts for Multiple Object Generation

arXiv:2405.00791v1 Announce Type: new
Abstract: Large-scale text-to-image models that can generate high-quality and diverse images based on textual prompts have shown remarkable success. These models aim ultimately to create complex scenes, and addressing the challenge of multi-subject generation is a critical step towards this goal. However, the existing state-of-the-art diffusion models face difficulty when generating images that involve multiple subjects. When presented with a prompt containing more than one subject, these models may omit some subjects or merge them together. …

abstract aim art arxiv challenge create cs.ai cs.cv diffusion diffusion models diverse face generate however image images multiple object prompts quality scale state success text text-to-image textual type