Towards Zero-Shot Point Cloud Registration Across Diverse Scales, Scenes, and Sensor Setups
跨多样尺度、场景和传感器设置的零样本点云配准
机构 * Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology（信息与决策系统实验室，麻省理工学院） ； Department of Computer Science and Engineering, Seoul National University（计算机科学与工程系，首尔国立大学）
专题命中 激光雷达 ：LiDAR(abstract)；分类 cs.RO、cs.CV
AI总结 提出BUFFER-X框架，通过几何自举、分布感知采样和坐标归一化实现零样本点云配准，同时引入BUFFER-X-Lite提升效率，适用于多样场景和传感器设置。
Comments 18 pages, 15 figures. Extended version of our ICCV 2025 highlight paper [arXiv:2503.07940]. arXiv admin note: substantial text overlap with arXiv:2503.07940
