Results 31 to 40 of about 1,073,958 (334)
RE-PU: A Self-Supervised Arbitrary-Scale Point Cloud Upsampling Method Based on Reconstruction
Applied SciencesThe point clouds obtained directly from three-dimensional scanning devices are often sparse and noisy. Therefore, point cloud upsampling plays an increasingly crucial role in fields such as point cloud reconstruction and rendering.
Yazhen Han +3 more
doaj +1 more source
, 2019 We present RL-GAN-Net, where a reinforcement learning (RL) agent provides fast and robust control of a generative adversarial network (GAN). Our framework is applied to point cloud shape completion that converts noisy, partial point cloud data into a ...
Kim, Young Min +2 more
core +1 more source
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
A Novel Method for Density Analysis of Repaired Point Cloud with Holes Based on Image Data
Remote Sensing, 2021 Repairing point cloud holes has become an important problem in the research of 3D laser point cloud data, which ensures the integrity and improves the precision of point cloud data.
Yibo He, Zhenqi Hu, Kan Wu, Rui Wang
doaj +1 more source
3D point cloud video segmentation oriented to the analysis of interactions [PDF]
, 2016 Given the widespread availability of point cloud data from consumer depth sensors, 3D point cloud segmentation becomes a promising building block for high level applications such as scene understanding and interaction analysis.
Casas Pla, Josep Ramon +2 more
core +1 more source
Power-Line Extraction Method for UAV Point Cloud Based on Region Growing Algorithm
南方能源建设, 2023 [Introduction] Since the power line has the characteristics of long transmission distance and a complex spatial environment, the UAV LiDAR point cloud technology can completely and efficiently obtain the geometric information of the power line and its ...
Xingyi LI, Wei WU, Zhiyao ZHAO
doaj +1 more source
Deep Projective 3D Semantic Segmentation
, 2017 Semantic segmentation of 3D point clouds is a challenging problem with numerous real-world applications. While deep learning has revolutionized the field of image semantic segmentation, its impact on point cloud data has been limited so far.
AE Johnson +6 more
core +1 more source
Colored Point Cloud Completion for a Head Using Adversarial Rendered Image Loss
Journal of Imaging, 2022 Recent advances in depth measurement and its utilization have made point cloud processing more critical. Additionally, the human head is essential for communication, and its three-dimensional data are expected to be utilized in this regard.
Yuki Ishida +2 more
doaj +1 more source
Bridging the gap: Multi‐stakeholder perspectives of molecular diagnostics in oncology
Molecular Oncology, EarlyView.Although molecular diagnostics is transforming cancer care, implementing novel technologies remains challenging. This study identifies unmet needs and technology requirements through a two‐step stakeholder involvement. Liquid biopsies for monitoring applications and predictive biomarker testing emerge as key unmet needs. Technology requirements vary by
Jorine Arnouts +8 more
wiley +1 more source
Adaptive Clustering for Point Cloud
SensorsThe point cloud segmentation method plays an important role in practical applications, such as remote sensing, mobile robots, and 3D modeling. However, there are still some limitations to the current point cloud data segmentation method when applied to ...
Zitao Lin +6 more
doaj +1 more source