"IndoorCD: A Large-Scale Indoor 3D Point Cloud Change Detection Benchmark"
收藏DataCite Commons2026-02-25 更新2026-05-03 收录
下载链接：
https://ieee-dataport.org/documents/indoorcd-large-scale-indoor-3d-point-cloud-change-detection-benchmark
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资源简介：
"IndoorCD is a large-scale benchmark dataset for indoor 3D point cloud change detection. The dataset contains 1,018 scene pairs collected from 217 real-world indoor rooms using consumer-grade iPhone LiDAR sensors. IndoorCD provides object-level 3D bounding-box annotations and point-level change-labels for Add and Remove classes across multiple change scenarios.The dataset captures realistic indoor environments with natural sensor noise, occlusions, and varying object sizes. IndoorCD is designed to support research in change detection, robotics, and 3D computer vision.In addition to the dataset, baseline methods and evaluation tools are provided to facilitate reproducible research and standardised comparison.IndoorCD aims to advance the development and evaluation of indoor 3D change detection algorithms."
提供机构：
IEEE DataPort
创建时间：
2026-02-25
