Sequence Generation Completion Method and Resolution Scaling Network for Point Cloud Completion-Reference-Cited by-同舟云学术

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Sequence Generation Completion Method and Resolution Scaling Network for Point Cloud Completion

Published:2024 Issue: Volume:62 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Xu Jiabo¹^ORCID,Zhang Yirui²^ORCID,Zou Yanni³^ORCID,Liu Peter X.⁴^ORCID

Affiliation:

1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

2. School of Information Engineering, Nanchang University, Nanchang, China

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

4. Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10547329.pdf?arnumber=10547329

Reference71 articles.

1. Cross-city matters: A multimodal remote sensing benchmark dataset for cross-city semantic segmentation using high-resolution domain adaptation networks

2. More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

3. LRR-Net: An Interpretable Deep Unfolding Network for Hyperspectral Anomaly Detection

4. UIU-Net: U-Net in U-Net for Infrared Small Object Detection

5. GLORN: Strong Generalization Fully Convolutional Network for Low-Overlap Point Cloud Registration

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1. Accelerated forest modeling from tree canopy point clouds via deep learning;International Journal of Applied Earth Observation and Geoinformation;2024-08

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