Results 51 to 60 of about 165,702 (282)
3D Point Cloud Denoising via Deep Neural Network based Local Surface Estimation
, 2019 We present a neural-network-based architecture for 3D point cloud denoising called neural projection denoising (NPD). In our previous work, we proposed a two-stage denoising algorithm, which first estimates reference planes and follows by projecting ...
Chen, Siheng +2 more
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NICP: Dense normal based point cloud registration [PDF]
, 2015 In this paper we present a novel on-line method to recursively align point clouds. By considering each point together with the local features of the surface (normal and curvature), our method takes advantage of the 3D structure around the points for the ...
Grisetti, Giorgio, Serafin, Jacopo
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Fast and robust 3D feature extraction from sparse point clouds [PDF]
, 2016 Matching 3D point clouds, a critical operation in map building and localization, is difficult with Velodyne-type sensors due to the sparse and non-uniform point clouds that they produce.
GRISETTI, GIORGIO +2 more
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3D Component Segmentation Network and Dataset for Non-Cooperative Spacecraft
Aerospace, 2022 Spacecraft component segmentation is one of the key technologies which enables autonomous navigation and manipulation for non-cooperative spacecraft in OOS (On-Orbit Service). While most of the studies on spacecraft component segmentation are based on 2D
Guangyuan Zhao +4 more
doaj +1 more source
Pointwise Convolutional Neural Networks
, 2018 Deep learning with 3D data such as reconstructed point clouds and CAD models has received great research interests recently. However, the capability of using point clouds with convolutional neural network has been so far not fully explored. In this paper,
Hua, Binh-Son +2 more
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Tracking of secondary and temporary objects in structural concrete work [PDF]
, 2014 Previous research has shown that “Scan-vs-BIM ” object recognition systems, that fuse 3D point clouds from Terrestrial Laser Scanning (TLS) or digital photogrammetry with 4D project BIM, provide valuable information for tracking structural works. However,
Bosché, Frédéric +3 more
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3D Point Cloud Recognition Based on a Multi-View Convolutional Neural Network
Sensors, 2018 The recognition of three-dimensional (3D) lidar (light detection and ranging) point clouds remains a significant issue in point cloud processing. Traditional point cloud recognition employs the 3D point clouds from the whole object.
Le Zhang, Jian Sun, Qiang Zheng
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Unsupervised Domain Adaptation for 3D Point Clouds by Searched Transformations
IEEE Access, 2022 Input-level domain adaptation reduces the burden of a neural encoder without supervision by reducing the domain gap at the input level. Input-level domain adaptation is widely employed in 2D visual domain, e.g., images and videos, but is not utilized for
Dongmin Kang +3 more
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3D DATA ACQUISITION FOR INDOOR ASSETS USING TERRESTRIAL LASER SCANNING [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 The newly development of technology clearly shows an improvement of three-dimension (3D) data acquisition techniques. The requirements of 3D information and features have been obviously increased during past few years in many related fields.
S. Y. Lee, Z. Majid, H. Setan
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Point attention network for semantic segmentation of 3D point clouds [PDF]
Pattern Recognition, 2020 Submitted to a ...
Mingtao Feng +4 more
openaire +2 more sources