Robust Multiview Point Cloud Registration with Reliable Pose Graph Initialization and History Reweighting-Reference-Cited by-同舟云学术

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Robust Multiview Point Cloud Registration with Reliable Pose Graph Initialization and History Reweighting

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
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Author:

Wang Haiping¹,Liu Yuan²,Dong Zhen¹,Guo Yulan³,Liu Yu-Shen⁴,Wang Wenping⁵,Yang Bisheng¹

Affiliation:

1. Wuhan University

2. The University of Hong Kong

3. Sun Yat-sen University

4. Tsinghua University

5. Texas A&M University

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203551.pdf?arnumber=10203551

Reference59 articles.

1. Robust reconstruction of indoor scenes;choi;CVPR,2015

2. Deepgmr: Learning latent gaussian mixture models for registration;yuan;ECCV,2020

3. Sc2pcr: A second order spatial compatibility for efficient and robust point cloud registration;chen;CVPR,2022

4. Cofinet: Reliable coarse-to-fine correspondences for robust pointcloud registration;yu;NeurIPS,2021

5. Fully Convolutional Geometric Features

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2. PointTr: Low-Overlap Point Cloud Registration With Transformer;IEEE Sensors Journal;2024-04-15

3. Fully automated structured light scanning for high-fidelity 3D reconstruction via graph optimization;Optics Express;2024-02-28

4. A new method for point cloud registration: Adaptive relation-oriented convolution and recurrent correspondence-walk;Knowledge-Based Systems;2024-01

5. RegiFormer: Unsupervised Point Cloud Registration via Geometric Local-to-Global Transformer and Self-Augmentation;IEEE Transactions on Geoscience and Remote Sensing;2024

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