Semantic segmentation of 3d lidar data using deep learning: a review of projection-based methods
LiDAR sensor is an active remote sensing sensor that is increasingly used to capture 3D
information of real-world objects. Real-time decision-making applications such as …
information of real-world objects. Real-time decision-making applications such as …
Sampling-attention deep learning network with transfer learning for large-scale urban point cloud semantic segmentation
Targeting the development of smart cities to facilitate the significant analysis of large-scale
urban for construction and update. This research develops a new method named transfer …
urban for construction and update. This research develops a new method named transfer …
Improving performance of deep learning models for 3D point cloud semantic segmentation via attention mechanisms
Abstract 3D Semantic segmentation is a key element for a variety of applications in robotics
and autonomous vehicles. For such applications, 3D data are usually acquired by LiDAR …
and autonomous vehicles. For such applications, 3D data are usually acquired by LiDAR …
On power Jaccard losses for semantic segmentation
In this work, a new generalized loss function is proposed called power Jaccard to perform
semantic segmentation tasks. It is compared with classical loss functions in different …
semantic segmentation tasks. It is compared with classical loss functions in different …
Label3DMaize: toolkit for 3D point cloud data annotation of maize shoots
Background The 3D point cloud is the most direct and effective data form for studying plant
structure and morphology. In point cloud studies, the point cloud segmentation of individual …
structure and morphology. In point cloud studies, the point cloud segmentation of individual …
Large-scale 3D point-cloud semantic segmentation of urban and rural scenes using data volume decomposition coupled with pipeline parallelism
AWZ Chew, A Ji, L Zhang - Automation in construction, 2022 - Elsevier
This study proposes a generic approach which performs a series of systematic analyses by
first introducing a data volume decomposition method to generate useful data features for …
first introducing a data volume decomposition method to generate useful data features for …
PIG-Net: Inception based deep learning architecture for 3D point cloud segmentation
Point clouds, being the simple and compact representation of surface geometry of 3D
objects, have gained increasing popularity with the evolution of deep learning networks for …
objects, have gained increasing popularity with the evolution of deep learning networks for …
The use of CNNs in VR/AR/MR/XR: a systematic literature review
This study offers a systematic literature review on the application of Convolutional Neural
Networks in Virtual Reality, Augmented Reality, Mixed Reality, and Extended Reality …
Networks in Virtual Reality, Augmented Reality, Mixed Reality, and Extended Reality …
Semantic segmentation network with multi-path structure, attention reweighting and multi-scale encoding
Z Lin, W Sun, B Tang, J Li, X Yao, Y Li - The Visual Computer, 2023 - Springer
Semantic segmentation is an active field of computer vision. It provides semantic information
for many applications. In semantic segmentation tasks, spatial information, context …
for many applications. In semantic segmentation tasks, spatial information, context …
Automatic generation of large-scale 3D road networks based on GIS data
How to automatically generate a realistic large-scale 3D road network is a key point for
immersive and credible traffic simulations. Existing methods cannot automatically generate …
immersive and credible traffic simulations. Existing methods cannot automatically generate …