Enhancing Subject-Driven Image Synthesis by Mitigating Content Ignorance with Subject-Agnostic Guidance
Subject-driven text-to-image synthesis models often overlook crucial attributes specified in the text prompt due to the dominance of subject-specific information, leading to suboptimal content alignment. This work introduces Subject-Agnostic Guidance (SAG) to address this challenge by diminishing the influence of subject-specific attributes and enhancing attention towards subject-agnostic attributes.