PointDifformer: Robust Point Cloud Registration With Neural Diffusion and Transformer-Reference-Cited by-同舟云学术

PointDifformer: Robust Point Cloud Registration With Neural Diffusion and Transformer

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:

She Rui¹^ORCID,Kang Qiyu¹,Wang Sijie¹^ORCID,Tay Wee Peng¹^ORCID,Zhao Kai¹^ORCID,Song Yang¹^ORCID,Geng Tianyu¹,Xu Yi¹,Navarro Diego Navarro²,Hartmannsgruber Andreas²^ORCID

Affiliation:

1. School of Electrical and Electronic Engineering, Nanyang Technological University, Jurong West, Singapore

2. Continental Automotive Singapore Pte. Ltd., Suntec City, Singapore

Funder

Singapore Ministry of Education Academic Research Fund Tier 2

National Research Foundation, Singapore, and Infocomm Media Development Authority Under Its Future Communications Research and Development Program

RIE2020 Industry Alignment Fund-Industry Collaboration Projects (IAF-ICP) Funding Initiative [cash and in-kind contribution from the industry partner(s)]

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10384401.pdf?arnumber=10384401

Reference95 articles.

1. Efficient Pairwise 3-D Registration of Urban Scenes via Hybrid Structural Descriptors

2. Compatibility-Guided Sampling Consensus for 3-D Point Cloud Registration

3. Location Learning for AVs: LiDAR and Image Landmarks Fusion Localization with Graph Neural Networks

4. A Weakly Supervised Graph Deep Learning Framework for Point Cloud Registration

5. T-LOAM: Truncated Least Squares LiDAR-Only Odometry and Mapping in Real Time

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advancing 3D point cloud understanding through deep transfer learning: A comprehensive survey;Information Fusion;2025-01

2. DBDNet:Partial-to-partial point cloud registration with dual branches decoupling;Knowledge-Based Systems;2024-07

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

4. SUCOFT: Robust Point Cloud Registration Based on Guaranteed Supercore Maximization and Flexible Thresholding;IEEE Transactions on Geoscience and Remote Sensing;2024