Filtering-Assisted Airborne Point Cloud Semantic Segmentation for Transmission Lines [PDF]
SensorsPoint cloud semantic segmentation is crucial for identifying and analyzing transmission lines. Due to the number of point clouds being huge, complex scenes, and unbalanced sample proportion, the mainstream machine learning methods of point cloud ...
Wanjing Yan +5 more
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Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage: A Comprehensive Review [PDF]
Remote Sensing, 2023 In the cultural heritage field, point clouds, as important raw data of geomatics, are not only three-dimensional (3D) spatial presentations of 3D objects but they also have the potential to gradually advance towards an intelligent data structure with ...
Su Yang, Miaole Hou, Songnian Li
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Point mask transformer for outdoor point cloud semantic segmentation
Computational Visual MediaCurrent outdoor point-cloud segmentation methods typically formulate semantic segmentation as a per-point/voxel-classification task. Although this strategy is straightforward because it classifies each point directly, it ignores the overall relationship ...
Xiangqian Li +4 more
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FROM MULTI-VIEW TO POINT CLOUD SEGMENTATION: THE CASE STUDY OF VILLA ROBERTI BRUGINE [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Point cloud semantic segmentation is a key step for automatically deriving an informative building model from the 3D data reconstruction obtained by 3D surveying tools, such as laser scanners and photogrammetry. Such representation increases the richness
A. Masiero +3 more
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Semantic Segmentation Method for Sparse Point Clouds Based on Straight Flow Completion and Multi-Feature Fusion [PDF]
SensorsPoint cloud semantic segmentation is a vital task in 3D computer vision. However, the inherent sparsity of point clouds complicates the segmentation process.
Tong Zheng +4 more
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IEEE Access, 2023 As a critical step in 3D scene understanding, semantic segmentation of point clouds has broad application scenarios, including intelligent driving, augmented reality, smart factories, etc.
Ansi Zhang +4 more
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A Review of Deep Learning-Based Semantic Segmentation for Point Cloud
IEEE Access, 2019 In recent years, the popularity of depth sensors and 3D scanners has led to a rapid development of 3D point clouds. Semantic segmentation of point cloud, as a key step in understanding 3D scenes, has attracted extensive attention of researchers.
Jiaying Zhang +3 more
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Point Cloud Semantic Segmentation Method Based on Block Feature Fusion [PDF]
Jisuanji gongcheng, 2022 A semantic segmentation method integrating block features is proposed to reduce the computational complexity of semantic segmentation of multi-class 3D objects in outdoor large-scale point cloud scenes.The square grid segmentation method is used to ...
GAO Qingji, LI Tianhao, XING Zhiwei, LIU Peipei
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SEMANTIC ENRICHMENT OF 3D POINT CLOUDS USING 2D IMAGE SEGMENTATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 3D point cloud segmentation is computationally intensive due to the lack of inherent structural information and the unstructured nature of the point cloud data, which hinders the identification and connection of neighboring points.
A. Rai +3 more
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JSMNET: IMPROVING INDOOR POINT CLOUD SEMANTIC AND INSTANCE SEGMENTATION THROUGH SELF-ATTENTION AND MULTISCALE FUSION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 The semantic understanding of indoor 3D point cloud data is crucial for a range of subsequent applications, including indoor service robots, navigation systems, and digital twin engineering. Global features are crucial for achieving high-quality semantic
S. Xu, S. Xu, Z. Zhang, Z. Zhang
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