Scaling Up Personalized Image Aesthetic Assessment via Task Vector Customization

Understand

The task of personalized image aesthetic assessment seeks to tailor aesthetic score prediction models to match individual preferences with just a few user-provided inputs.

• However, the scalability and generalization capabilities of current approaches are considerably restricted by their reliance on an expensive curated database.
• To overcome this long-standing scalability challenge, we present a unique approach that leverages readily available databases for general image aesthetic assessment and image quality assessment.
• Specifically, we view each database as a distinct image score regression task that exhibits varying degrees of personalization potential.