VisualCritic: Making LMMs Perceive Visual Quality Like Humans

Understand

At present, large multimodal models (LMMs) have exhibited impressive generalization capabilities in understanding and generating visual signals.

• However, they currently still lack sufficient capability to perceive low-level visual quality akin to human perception.
• Can LMMs achieve this and show the same degree of generalization in this regard? If so, not only could the versatility of LMMs be further enhanced, but also the challenge of poor cross-dataset performance in the field of visual quality assessment could be addressed.
• In this paper, we explore this question and provide the answer "Yes!".