Cargando…
Spatial Aggregation Net: Point Cloud Semantic Segmentation Based on Multi-Directional Convolution
Semantic segmentation of 3D point clouds plays a vital role in autonomous driving, 3D maps, and smart cities, etc. Recent work such as PointSIFT shows that spatial structure information can improve the performance of semantic segmentation. Motivated by this phenomenon, we propose Spatial Aggregation...
Autores principales: | Cai, Guorong, Jiang, Zuning, Wang, Zongyue, Huang, Shangfeng, Chen, Kai, Ge, Xuyang, Wu, Yundong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806191/ https://www.ncbi.nlm.nih.gov/pubmed/31591349 http://dx.doi.org/10.3390/s19194329 |
Ejemplares similares
-
Point Cloud Semantic Segmentation Network Based on Multi-Scale Feature Fusion
por: Du, Jing, et al.
Publicado: (2021) -
PSegNet: Simultaneous Semantic and Instance Segmentation for Point Clouds of Plants
por: Li, Dawei, et al.
Publicado: (2022) -
FGCN: Image-Fused Point Cloud Semantic Segmentation with Fusion Graph Convolutional Network
por: Zhang, Kun, et al.
Publicado: (2023) -
Semantic Segmentation of Natural Materials on a Point Cloud Using Spatial and Multispectral Features
por: Jurado, J. M., et al.
Publicado: (2020) -
FF-Net: Feature-Fusion-Based Network for Semantic Segmentation of 3D Plant Point Cloud
por: Guo, Xindong, et al.
Publicado: (2023)