AI RESEARCH
QD-PCQA: Quality-Aware Domain Adaptation for Point Cloud Quality Assessment
arXiv CS.CV
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ArXi:2603.03726v2 Announce Type: replace No-Reference Point Cloud Quality Assessment (NR-PCQA) still struggles with generalization, primarily due to the scarcity of annotated point cloud datasets. Since the Human Visual System (HVS) drives perceptual quality assessment independently of media types, prior knowledge on quality learned from images can be repurposed for point clouds. This insight motivates adopting Unsupervised Domain Adaptation (UDA) to transfer quality-relevant priors from labeled images to unlabeled point clouds.