UniPercept: Unified Perceptual Image Understanding

This paper addresses a critical limitation of current Multimodal Large Language Models (MLLMs): their limited ability to understand perceptual-level image features. It introduces a novel framework, UniPercept-Bench, and a baseline model, UniPercept, to improve understanding across aesthetics, quality, structure, and texture. The work's significance lies in defining perceptual-level image understanding in the context of MLLMs and providing a benchmark and baseline for future research. This is important because it moves beyond basic visual tasks to more nuanced understanding, which is crucial for applications like image generation and editing.