A Survey on Deep Learning Based Segmentation, Detection and Classification for 3D Point Clouds

Autor:	Prasoon Kumar Vinodkumar, Dogus Karabulut, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	deep learning 3D object recognition 3D object segmentation 3D object detection 3D object classification Science Astrophysics QB460-466 Physics QC1-999
Zdroj:	Entropy, Vol 25, Iss 4, p 635 (2023)
Druh dokumentu:	article
ISSN:	1099-4300
DOI:	10.3390/e25040635
Popis:	The computer vision, graphics, and machine learning research groups have given a significant amount of focus to 3D object recognition (segmentation, detection, and classification). Deep learning approaches have lately emerged as the preferred method for 3D segmentation problems as a result of their outstanding performance in 2D computer vision. As a result, many innovative approaches have been proposed and validated on multiple benchmark datasets. This study offers an in-depth assessment of the latest developments in deep learning-based 3D object recognition. We discuss the most well-known 3D object recognition models, along with evaluations of their distinctive qualities.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/35089c037cc04d079d61b9930f8af6cb Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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