Stellar: Systematic Evaluation of Human-Centric Personalized Text-to-Image Methods

Understand

In this work, we systematically study the problem of personalized text-to-image generation, where the output image is expected to portray information about specific human subjects.

• E.g., generating images of oneself appearing at imaginative places, interacting with various items, or engaging in fictional activities.
• To this end, we focus on text-to-image systems that input a single image of an individual to ground the generation process along with text describing the desired visual context.
• Our first contribution is to fill the literature gap by curating high-quality, appropriate data for this task.