13 citations · 14 across the 3 of their papers we have counts for
3 papers
cs.CV2025★ 13 cited
Impact of color and mixing proportion of synthetic point clouds on semantic segmentation
Shaojie Zhou, Jia-Rui Lin, Peng Pan +2
Deep learning (DL)-based point cloud segmentation is essential for understanding built environment. Despite synthetic point clouds (SPC) having the potential to compensate for data…
cs.CV2024
Scan-to-BIM for As-built Roads: Automatic Road Digital Twinning from Semantically Labeled Point Cloud Data
Yuexiong Ding, Mengtian Yin, Ran Wei +3
Creating geometric digital twins (gDT) for as-built roads still faces many challenges, such as low automation level and accuracy, limited asset types and shapes, and reliance on en…
cs.CV2023★ 1 cited
GeoSpark: Sparking up Point Cloud Segmentation with Geometry Clue
Zhening Huang, Xiaoyang Wu, Hengshuang Zhao +4
Current point cloud segmentation architectures suffer from limited long-range feature modeling, as they mostly rely on aggregating information with local neighborhoods. Furthermore…