广东工业大学学报2025，Vol.42Issue(4)：20-28,9.DOI:10.12052/gdutxb.240133
融合三维高斯点染和分数蒸馏采样的三维点云补全方法
3D Point Cloud Completion Method Integrating 3D Gaussian Splatting and Score Distillation Sampling
摘要
Abstract
This study addressed the limitations of existing 3D point cloud completion methods,which rely on paired data and supervised learning,resulting in high data costs and limited generalization capabilities.This paper proposed a novel 3D point cloud completion method without requiring paired data for training by integrating 3D Gaussian splatting and Score Distillation Sampling(SDS)techniques.In the proposed method,incomplete point clouds were transformed into 3D Gaussian models,which were iteratively optimized using a pre-trained 2D diffusion model to predict complete point clouds and fulfill the completion task.To enhance the initial 3D Gaussian models,the authors introduced a point densification technique that increased the density of input point clouds.Additionally,a progressive camera sampling strategy was adopted during the early optimization stages to control the camera sampling range,thereby improving optimization efficiency.The experimental results demonstrate that the proposed method outperforms existing approaches on the RedWood-3DScan dataset.Ablation studies further validate the effectiveness of the optimization strategies,confirming the superiority of the proposed method in handling real-world data.关键词
点云补全/三维高斯点染/分数蒸馏采样/预训练二维扩散模型Key words
point cloud completion/3D gaussian splatting/score distillation sampling/pre-trained 2D diffusion model分类
信息技术与安全科学引用本文复制引用
刘立程,刘柏菁,潘丹,曾安,杨宝瑶,赵靖亮..融合三维高斯点染和分数蒸馏采样的三维点云补全方法[J].广东工业大学学报,2025,42(4):20-28,9.基金项目
广东省重点领域研发计划项目(2021B0101220006) （2021B0101220006）
国家自然科学基金资助项目(61976058,62102098) （61976058,62102098）
广东省科技计划项目(2019A050510041) （2019A050510041）
广东省自然科学基金资助项目(2021A1515012300) （2021A1515012300）
广东省基础与应用基础研究区域联合基金资助项目(2022A1515140096) （2022A1515140096）
广州市科技计划项目(202103000034,202201010266) （202103000034,202201010266）
