Ripe with possibilities offered by deep-learning techniques and useful in applications related to remote sensing, computer vision, and robotics, 3D point cloud semantic segmentation (PCSS) and point cloud segmentation (PCS) are attracting increasing interest. This article summarizes available data sets and relevant studies on recent developments in PCSS and PCS.
Beschreibung
Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation | IEEE Journals & Magazine | IEEE Xplore
%0 Journal Article
%1 9028090
%A Xie, Yuxing
%A Tian, Jiaojiao
%A Zhu, Xiao Xiang
%D 2020
%J IEEE Geoscience and Remote Sensing Magazine
%K 2020 3D point-cloud review segmentation semantic
%N 4
%P 38-59
%R 10.1109/MGRS.2019.2937630
%T Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation
%U https://ieeexplore.ieee.org/document/9028090
%V 8
%X Ripe with possibilities offered by deep-learning techniques and useful in applications related to remote sensing, computer vision, and robotics, 3D point cloud semantic segmentation (PCSS) and point cloud segmentation (PCS) are attracting increasing interest. This article summarizes available data sets and relevant studies on recent developments in PCSS and PCS.
@article{9028090,
abstract = {Ripe with possibilities offered by deep-learning techniques and useful in applications related to remote sensing, computer vision, and robotics, 3D point cloud semantic segmentation (PCSS) and point cloud segmentation (PCS) are attracting increasing interest. This article summarizes available data sets and relevant studies on recent developments in PCSS and PCS.},
added-at = {2021-06-02T09:41:42.000+0200},
author = {Xie, Yuxing and Tian, Jiaojiao and Zhu, Xiao Xiang},
biburl = {https://www.bibsonomy.org/bibtex/20505aa6cc15fe25e02b15f4bc2633ff4/analyst},
description = {Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation | IEEE Journals & Magazine | IEEE Xplore},
doi = {10.1109/MGRS.2019.2937630},
interhash = {64e295d092a1c09051a06d7895696169},
intrahash = {0505aa6cc15fe25e02b15f4bc2633ff4},
issn = {2168-6831},
journal = {IEEE Geoscience and Remote Sensing Magazine},
keywords = {2020 3D point-cloud review segmentation semantic},
month = dec,
number = 4,
pages = {38-59},
timestamp = {2021-06-02T09:41:42.000+0200},
title = {Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation},
url = {https://ieeexplore.ieee.org/document/9028090},
volume = 8,
year = 2020
}