PointQ-Bench: Benchmarking Diagnostic and Interpretable Point Cloud Quality Assessment
Point cloud quality plays a critical role in 3D acquisition, reconstruction, rendering, and perception, yet existing point cloud quality assessment (PCQA) research remains largely centered on scalar score prediction. In practical inspection scenarios, quality assessment often involves identifying defects, characterizing dominant issue types, assessing downstream usability, and providing evidence-supported descriptions, which are not explicitly evaluated by current benchmarks. We introduce PointQ-Bench, a benchmark designed to extend PCQA from scalar scoring toward comprehensive quality understanding. PointQ-Bench consists of 3,083 point clouds spanning authentic scans, simulated distortio...
| Authors | Duanchu Wang, Cheng Li, Junjie Yang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 27 May 2026 |
| Last updated at source | 5 September 2026 |
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