Semantic Segmentation of Point Cloud With Novel Neural Radiation Field Convolution-Reference-Cited by-同舟云学术

Semantic Segmentation of Point Cloud With Novel Neural Radiation Field Convolution

Published:2023 Issue: Volume:20 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Li Wei¹,Zhan Lixin²,Min Weidong³^ORCID,Zou Yi²,Huang Zheng²,Wen Chenglu⁴^ORCID

Affiliation:

1. School of Software, Nanchang University, Nanchang, China

2. School of Mathematics and Computer Science, Nanchang University, Nanchang, China

3. School of Mathematics and Computer Science and Institute of Metaverse, Nanchang University, Nanchang, China

4. School of Informatics, Xiamen University, Xiamen, China

Funder

National Natural Science Foundation of Jiangxi Province

National Natural Science Foundation of China

Jiangxi Key Laboratory of Smart City

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10034981/10226312.pdf?arnumber=10226312

Reference16 articles.

1. Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning

2. SCF-Net: Learning Spatial Contextual Features for Large-Scale Point Cloud Segmentation

3. SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

4. Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges

5. Spherical coordinate transformation-embedded deep network for primitive instance segmentation of point clouds;li;Int J Appl Earth Observ Geoinf,2022

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