AI RESEARCH

R4-CGQA: Retrieval-based Vision Language Models for Computer Graphics Image Quality Assessment

arXiv CS.CV

ArXi:2603.10578v1 Announce Type: new Immersive Computer Graphics (CGs) rendering has become ubiquitous in modern daily life. However, comprehensively evaluating CG quality remains challenging for two reasons: First, existing CG datasets lack systematic descriptions of rendering quality; and second existing CG quality assessment methods cannot provide reasonable text-based explanations. To address these issues, we first identify six key perceptual dimensions of CG quality from the user perspective and construct a dataset of 3500 CG images with corresponding quality descriptions.