Results 51 to 60 of about 528,144 (284)
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
core +1 more source
From 3D Point Clouds to Pose-Normalised Depth Maps [PDF]
, 2010 We consider the problem of generating either pairwise-aligned or pose-normalised depth maps from noisy 3D point clouds in a relatively unrestricted poses. Our system is deployed in a 3D face alignment application and consists of the following four stages:
Heseltine, Tom +2 more
core +1 more source
IEEE Communications MagazineAcquisition and processing of point clouds (PCs) is a crucial enabler for many emerging applications reliant on 3D spatial data, such as robot navigation, autonomous vehicles, and augmented reality. In most scenarios, PCs acquired by remote sensors must be transmitted to an edge server for fusion, segmentation, or inference.
Yulin Shao +5 more
openaire +2 more sources
Topological Point Cloud Clustering
CoRR, 2023 Accepted at the 40th International Conference on Machine Learning (ICML), 2023.
Grande, Vincent P., Schaub, Michael T.
openaire +4 more sources
Towards online mobile mapping using inhomogeneous lidar data [PDF]
, 2016 In this paper we present a novel approach to quickly obtain detailed 3D reconstructions of large scale environments. The method is based on the consecutive registration of 3D point clouds generated by modern lidar scanners such as the Velodyne HDL-32e or
Goeman, Werner +4 more
core +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Since 2017, many deep learning methods for 3-D point clouds observed by airborne LiDAR (airborne 3-D point clouds) have been proposed. Moreover, not only a deep learning method for airborne 3-D point clouds but also a deep learning method for points and ...
Takayuki Shinohara +2 more
doaj +1 more source
SEGCloud: Semantic Segmentation of 3D Point Clouds
, 2017 3D semantic scene labeling is fundamental to agents operating in the real world. In particular, labeling raw 3D point sets from sensors provides fine-grained semantics.
Armeni, Iro +4 more
core +1 more source
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
core +1 more source
Revealing the structure of land plant photosystem II: the journey from negative‐stain EM to cryo‐EM
FEBS Letters, EarlyView.Advances in cryo‐EM have revealed the detailed structure of Photosystem II, a key protein complex driving photosynthesis. This review traces the journey from early low‐resolution images to high‐resolution models, highlighting how these discoveries deepen our understanding of light harvesting and energy conversion in plants.
Roman Kouřil
wiley +1 more source
Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment
Molecular Oncology, EarlyView.This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley +1 more source