Results 71 to 80 of about 6,391,115 (351)
OctAttention: Octree-based Large-scale Contexts Model for Point Cloud Compression [PDF]
AAAI Conference on Artificial Intelligence, 2022 In point cloud compression, sufficient contexts are significant for modeling the point cloud distribution. However, the contexts gathered by the previous voxel-based methods decrease when handling sparse point clouds.
Chunyang Fu +4 more
semanticscholar +1 more source
Linear-Based Incremental Co-Registration of MLS and Photogrammetric Point Clouds
Remote Sensing, 2021 Today, mobile laser scanning and oblique photogrammetry are two standard urban remote sensing acquisition methods, and the cross-source point-cloud data obtained using these methods have significant differences and complementarity.
Shiming Li +4 more
doaj +1 more source
Cloud Point Extraction in the Determination of Drugs in Biological Matrices.
Journal of Chromatographic Science, 2020 Cloud point extraction (CPE) is a simple, safe and environment-friendly technique used in the preparation of various samples. It was primarily developed for the assessment of environmental samples, especially analyzed for metals. Recently, this technique
Grzegorz Kojro, P. Wroczynski
semanticscholar +1 more source
TEASER: Fast and Certifiable Point Cloud Registration [PDF]
IEEE Transactions on robotics, 2020 We propose the first fast and certifiable algorithm for the registration of two sets of three-dimensional (3-D) points in the presence of large amounts of outlier correspondences.
Heng Yang, J. Shi, L. Carlone
semanticscholar +1 more source
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
End-to-End Point Cloud Completion Network with Attention Mechanism
Sensors, 2022 We propose a conceptually simple, general framework and end-to-end approach to point cloud completion, entitled PCA-Net. This approach differs from the existing methods in that it does not require a “simple” network, such as multilayer perceptrons (MLPs),
Yaqin Li +4 more
doaj +1 more source
Projection-Based Point Convolution for Efficient Point Cloud Segmentation
IEEE Access, 2022 Understanding point cloud has recently gained huge interests following the development of 3D scanning devices and the accumulation of large-scale 3D data.
Pyunghwan Ahn +4 more
doaj +1 more source
DENOISING OF 3D POINT CLOUDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Abstract. A method to remove random errors from 3D point clouds is proposed. It is based on the estimation of a local geometric descriptor of each point. For mobile mapping LiDAR and airborne LiDAR, a combined standard mesurement uncertainty of the LiDAR system may supplement a geometric approach.
E. Mugner, N. Seube
openaire +4 more sources
, 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
Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion
Remote Sensing, 2022 The point cloud data from actual measurements are often sparse and incomplete, making it difficult to apply them directly to visual processing and 3D reconstruction.
Ruidong Hao +6 more
doaj +1 more source