Reasoning in Vision-Language Models for Blind Image Quality Assessment

This research focuses on improving the reasoning capabilities of Vision-Language Models (VLMs) for the challenging task of Blind Image Quality Assessment (BIQA). The paper likely explores how VLMs can understand and evaluate image quality without explicit prior knowledge of image degradation.

• •Focuses on improving VLM reasoning for BIQA.
• •Explores how VLMs assess image quality without prior degradation knowledge.
• •Likely involves training or adaptation of VLMs for this specific task.