GLORN: Strong Generalization Fully Convolutional Network for Low-Overlap Point Cloud Registration-Reference-Cited by-同舟云学术

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

Published:2022 Issue: Volume:60 Page:1-14
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,Huang Yukun²^ORCID,Wan Zeyun¹,Wei Jingbo³^ORCID

Affiliation:

1. School of Mathematics and Computer Sciences, Nanchang University, Nanchang, China

2. School of Information Management, Jiangxi University of Finance and Economics, Nanchang, China

3. Institute of Space Science and Technology, Nanchang University, Nanchang, China

Funder

National Natural Science Foundation of China

Jiangxi Provincial Water Conservancy Science and Technology Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09896915.pdf?arnumber=9896915

Reference37 articles.

1. PPFNet: Global Context Aware Local Features for Robust 3D Point Matching

2. KPConv: Flexible and Deformable Convolution for Point Clouds

3. REGTR: End-to-end Point Cloud Correspondences with Transformers

4. CoFiNet: Reliable coarse-to-fine correspondences for robust pointcloud registration;yu;Proc Adv Neural Inf Process Syst,2021

5. 3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration

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2. Online LiDAR-camera extrinsic parameters self-checking and recalibration;Measurement Science and Technology;2024-07-30

3. Deep learning-based low overlap point cloud registration for complex scenario: The review;Information Fusion;2024-07

4. Addressing the generalization of 3D registration methods with a featureless baseline and an unbiased benchmark;Machine Vision and Applications;2024-03-23

5. Semantic enhancement based adaptive geometric encoding network for low overlap point cloud registration;Displays;2024-01

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