EGNet: 3D Semantic Segmentation Through Point–Voxel–Mesh Data for Euclidean–Geodesic Feature Fusion

EGNet: 3D Semantic Segmentation Through Point–Voxel–Mesh Data for Euclidean–Geodesic Feature Fusion

With the advancement of service robot technology, the demand for higher boundary precision in indoor semantic segmentation has increased. Traditional methods of extracting Euclidean features using point cloud and voxel data often neglect geodesic information, reducing boundary accuracy for adjacent...

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Bibliographic Details
Main Authors: Qi Li, Yu Song, Xiaoqian Jin, Yan Wu, Hang Zhang, Di Zhao
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
geodesic information
neural network
point cloud
semantic segmentation
voxel data
Online Access:https://www.mdpi.com/1424-8220/24/24/8196
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