Enhancing Descriptive Image Quality Assessment with A Large-scale Multi-modal Dataset

Understand

With the rapid advancement of Vision Language Models (VLMs), VLM-based Image Quality Assessment (IQA) seeks to describe image quality linguistically to align with human expression and capture the multifaceted nature of IQA tasks.

• However, current methods are still far from practical usage.
• First, prior works focus narrowly on specific sub-tasks or settings, which do not align with diverse real-world applications.
• Second, their performance is sub-optimal due to limitations in dataset coverage, scale, and quality.