How Control Information Influences Multilingual Text Image Generation and Editing?

Understand

Visual text generation has significantly advanced through diffusion models aimed at producing images with readable and realistic text.

• Recent works primarily use a ControlNet-based framework, employing standard font text images to control diffusion models.
• Recognizing the critical role of control information in generating high-quality text, we investigate its influence from three perspectives: input encoding, role at different stages, and output features.
• Our findings reveal that: 1) Input control information has unique characteristics compared to conventional inputs like Canny edges and depth maps.