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Instance Segmentation of LiDAR Point Clouds [PDF]
2020 IEEE International Conference on Robotics and Automation (ICRA), 2020 We propose a robust baseline method for instance segmentation which are specially designed for large-scale outdoor LiDAR point clouds. Our method includes a novel dense feature encoding technique, allowing the localization and segmentation of small, far-away objects, a simple but effective solution for single-shot instance prediction and effective ...
Feihu Zhang +6 more
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Hypergraph Position Attention Convolution Networks for 3D Point Cloud Segmentation [PDF]
Applied SciencesPoint cloud segmentation, as the basis for 3D scene understanding and analysis, has made significant progress in recent years. Graph-based modeling and learning methods have played an important role in point cloud segmentation.
Yanpeng Rong +5 more
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Learning to Optimally Segment Point Clouds [PDF]
IEEE Robotics and Automation Letters, 2020 We focus on the problem of class-agnostic instance segmentation of LiDAR point clouds. We propose an approach that combines graph-theoretic search with data-driven learning: it searches over a set of candidate segmentations and returns one where individual segments score well according to a data-driven point-based model of "objectness".
Peiyun Hu, David Held, Deva Ramanan
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FROM MULTI-VIEW TO POINT CLOUD SEGMENTATION: THE CASE STUDY OF VILLA ROBERTI BRUGINE [PDF]
, 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
Tucci, G. +3 more
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Three-dimensional Point Cloud Model Segmentation Based on Significance and Weak Convexity [PDF]
Jisuanji gongcheng, 2018 The existing three-dimensional point cloud model segmentation algorithms cannot segment large components and small components at the same time.Aiming at this problem,in this paper,a segmentation method is proposed based on the significance and weak ...
ZHENG Lele,HAN Huiyan,HAN Xie
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Nonlocal segmentation of point clouds with graphs [PDF]
2013 IEEE Global Conference on Signal and Information Processing, 2013 In this paper, we propose a nonlocal approach based on graphs to segment raw point clouds as a particular class of graph signals. Using the framework of Partial difference Equations (PdEs), we propose a transcription on graphs of recent continuous global active contours along with a minimization algorithm.
Francois Lozes +3 more
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Splitting and Merging Based Multi-model Fitting for Point Cloud Segmentation [PDF]
Journal of Geodesy and Geoinformation Science, 2019 This paper deals with the massive point cloud segmentation processing technology on the basis of machine vision, which is the second essential factor for the intelligent data processing of three dimensional conformation in digital photogrammetry. In this
Liangpei ZHANG,Yun ZHANG,Zhenzhong CHEN,Peipei XIAO,Bin LUO
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Projection-Based Point Convolution for Efficient Point Cloud Segmentation [PDF]
IEEE Access, 2022 Published in IEEE Access (Early Access)
Pyunghwan Ahn +4 more
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Voxel Cloud Connectivity Segmentation - Supervoxels for Point Clouds [PDF]
2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013 Unsupervised over-segmentation of an image into regions of perceptually similar pixels, known as super pixels, is a widely used preprocessing step in segmentation algorithms. Super pixel methods reduce the number of regions that must be considered later by more computationally expensive algorithms, with a minimal loss of information.
Papon J. +3 more
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Machine learning-based segmentation of aerial LiDAR point cloud data on building roof [PDF]
, 2023 Three-dimensional (3D) reconstruction of a building can be facilitated by correctly segmenting different feature points (e.g. in the form of boundary, fold edge, and planar points) over the building roof, and then, establishing relationships among the ...
Bela Stantic +11 more
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