Towards Better Text-to-Image Generation Alignment via Attention Modulation

Understand

In text-to-image generation tasks, the advancements of diffusion models have facilitated the fidelity of generated results.

• However, these models encounter challenges when processing text prompts containing multiple entities and attributes.
• The uneven distribution of attention results in the issues of entity leakage and attribute misalignment.
• Training from scratch to address this issue requires numerous labeled data and is resource-consuming.