MM-PCQA: Multi-Modal Learning for No-reference Point Cloud Quality Assessment. (arXiv:2209.00244v1 [cs.CV])

The visual quality of point clouds has been greatly emphasized since the
ever-increasing 3D vision applications are expected to provide cost-effective
and high-quality experiences for users. Looking back on the development of
point cloud quality assessment (PCQA) methods, the visual quality is usually
evaluated by utilizing single-modal information, i.e., either extracted from
the 2D projections or 3D point cloud. The 2D projections contain rich texture
and semantic information but are highly dependent on viewpoints, while the 3D
point clouds are …

arxiv cloud learning quality reference