TSG-Seg: Temporal-selective guidance for semi-supervised semantic segmentation of 3D LiDAR point clouds

LiDAR-based semantic scene understanding holds a pivotal role in various applications, including remote sensing and autonomous driving. However, the majority of LiDAR segmentation models rely on extensive and densely annotated training datasets, which is extremely laborious to annotate and hinder th...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	ISPRS journal of photogrammetry and remote sensing 2024-10, Vol.216, p.217-228
Hauptverfasser:	Xuan, Weihao, Qi, Heli, Xiao, Aoran
Format:	Artikel
Sprache:	eng
Schlagworte:	3D point cloud Autonomous driving data collection LiDAR photogrammetry Road scene understanding Semantic segmentation Semi-supervised learning Spatio-temporal learning
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!