DPR-Net: dual-branch probabilistic regression for no-reference point cloud quality assessment

Key Points

• The dual-branch probabilistic regression model significantly enhances point cloud quality assessment accuracy, achieving better evaluation results.
• Achieving improvements in point cloud quality assessment measures by 30% enhances reliability for various applications.
• This study presents a novel dual-branch probabilistic regression model, providing a methodical approach to evaluate point cloud data.
• Additional external validation is essential for broader applicability beyond the current dataset in assessing point cloud quality.