Conditional Score Guidance for Text-Driven Image-to-Image Translation

Understand

We present a novel algorithm for text-driven image-to-image translation based on a pretrained text-to-image diffusion model.

• Our method aims to generate a target image by selectively editing the regions of interest in a source image, defined by a modifying text, while preserving the remaining parts.
• In contrast to existing techniques that solely rely on a target prompt, we introduce a new score function that additionally considers both the source image and the source text prompt, tailored to address specific translation tasks.
• To this end, we derive the conditional score function in a principled manner, decomposing it into the standard score and a guiding term for target image generation.