Results 31 to 40 of about 165,702 (282)
3D‐FEGNet: A feature enhanced point cloud generation network from a single image
IET Computer Vision, 2023 Deep learning‐based single view 3D reconstruction is a hot topic in computer vision. However, predicting a more realistic 3D point cloud from a single image is an ill‐posed problem.
Ende Wang +4 more
doaj +1 more source
Leaves Segmentation in 3D Point Cloud [PDF]
, 2017 This paper presents a 3D plant segmentation method with an emphasis on segmentation of the leaves. This method is part of a 3D plant phenotyping project with a main objective that deals with the development of the leaf area over time. First, a 3D point cloud of a plant is obtained with Structure from Motion technique and the cloud is then segmented ...
Gelard, William +6 more
openaire +4 more sources
General Hypernetwork Framework for Creating 3D Point Clouds [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 In this work, we propose a novel method for generating 3D point clouds that leverages the properties of hypernetworks. Contrary to the existing methods that learn only the representation of a 3D object, our approach simultaneously finds a representation of the object and its 3D surface.
Przemyslaw Spurek +3 more
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Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning [PDF]
, 2019 We show that denoising of 3D point clouds can be learned unsupervised, directly from noisy 3D point cloud data only. This is achieved by extending recent ideas from learning of unsupervised image denoisers to unstructured 3D point clouds.
Hermosilla, Pedro +2 more
core +2 more sources
Machine Learning in LiDAR 3D Point Clouds [PDF]
, 2021 LiDAR point clouds contain measurements of complicated natural scenes and can be used to update digital elevation models, glacial monitoring, detecting faults and measuring uplift detecting, forest inventory, detect shoreline and beach volume changes, landslide risk analysis, habitat mapping, and urban development, among others.
Medina, F. Patricia, Paffenroth, Randy
openaire +2 more sources
Boundary-Aware graph Markov neural network for semiautomated object segmentation from point clouds
International Journal of Applied Earth Observations and Geoinformation, 2021 Due to the advantages of 3D point clouds over 2D optical images, the related researches on scene understanding in 3D point clouds have been increasingly attracting wide attention from academy and industry.
Huan Luo +6 more
doaj +1 more source
Geometric 3D point cloud compression [PDF]
Pattern Recognition Letters, 2014 This work has been supported by the Spanish Government DPI2013-40534-R grant.
Morell, Vicente +3 more
openaire +2 more sources
Difference of Normals as a Multi-Scale Operator in Unorganized Point Clouds [PDF]
, 2012 A novel multi-scale operator for unorganized 3D point clouds is introduced. The Difference of Normals (DoN) provides a computationally efficient, multi-scale approach to processing large unorganized 3D point clouds.
, +4 more
core +1 more source
Hierarchical Optimization of 3D Point Cloud Registration [PDF]
Sensors, 2020 Rigid registration of 3D point clouds is the key technology in robotics and computer vision. Most commonly, the iterative closest point (ICP) and its variants are employed for this task. These methods assume that the closest point is the corresponding point and lead to sensitivity to the outlier and initial pose, while they have poor computational ...
Liu, Huikai +5 more
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Nonparametric Regression for 3D Point Cloud Learning
Journal of machine learning research : JMLR, 2021 Over the past two decades, we have seen an exponentially increased amount of point clouds collected with irregular shapes in various areas. Motivated by the importance of solid modeling for point clouds, we develop a novel and efficient smoothing tool based on multivariate splines over the tetrahedral partitions to extract the underlying signal and ...
Li, Xinyi +5 more
openaire +3 more sources