A Review of Point Cloud 3D Object Detection Methods Based on Deep Learning
Wang, Xiyuan; Lin, Jie; Yang, Longrui; Wang, Sicong
2024
Conference Name38th CCF National Conference of Computer Applications, CCF NCCA 2023
Source PublicationCommunications in Computer and Information Science
Volume1959 CCIS
Pages30-39
Conference DateJuly 16, 2023 - July 20, 2023
Conference PlaceSuzhou, China
PublisherSpringer Science and Business Media Deutschland GmbH
AbstractBased on introducing the coupling relationship between deep learning and three-dimensional point clouds, this paper reviews the three characteristics and research problems of point clouds, randomness, sparsity, and unstructuredness, and discusses three-dimensional point cloud target detection based on deep neural networks, including point cloud detection techniques following graph convolution, detection techniques following the original point cloud, and detection algorithms based on fusion processing of graph convolution and the original point cloud. Focusing on future research direction and development, the field of point cloud analysis is currently undergoing further development through the application of deep learning techniques. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
KeywordConvolutional neural networks - Deep neural networks - Learning systems - Object detection - Object recognition - Semantic Segmentation - Semantics 3D object - 3D point cloud - Coupling relationships - Deep leaning - Object detection method - Point-clouds - Research problems - Semantic segmentation - Targets detection - Three-dimensional point clouds
DOI10.1007/978-981-99-8764-1_3
Indexed ByEI
Language英语
EI Accession Number20235215288801
EI KeywordsConvolution
EI Classification Number461.4 Ergonomics and Human Factors Engineering - 716.1 Information Theory and Signal Processing - 723.2 Data Processing and Image Processing - 723.4 Artificial Intelligence
ISSN1865-0929
Original literature typeConference article (CA)
Citation statistics
none
Document Type会议论文
Identifierhttps://ir.lut.edu.cn/handle/2XXMBERH/169323
Collection电气工程与信息工程学院
Corresponding AuthorLin, Jie
AffiliationCollege of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
First Author AffilicationLanzhou University of Technology
Corresponding Author AffilicationLanzhou University of Technology
Recommended Citation
GB/T 7714
Wang, Xiyuan,Lin, Jie,Yang, Longrui,et al. A Review of Point Cloud 3D Object Detection Methods Based on Deep Learning[C]:Springer Science and Business Media Deutschland GmbH,2024:30-39.
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