Robust Semi-Supervised Point Cloud Registration via Latent GMM-Based Correspondence

Robust Semi-Supervised Point Cloud Registration via Latent GMM-Based Correspondence

Due to the fact that point clouds are always corrupted by significant noise and large transformations, aligning two point clouds by deep neural networks is still challenging. This paper presents a semi-supervised point cloud registration (PCR) method for accurately estimating point correspondences a...

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Bibliographic Details
Main Authors: Zhengyan Zhang, Erli Lyu, Zhe Min, Ang Zhang, Yue Yu, Max Q.-H. Meng
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Remote Sensing
Subjects:
point cloud registration
deep learning methods
Gaussian mixture model
semi-supervised learning
Online Access:https://www.mdpi.com/2072-4292/15/18/4493

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https://www.mdpi.com/2072-4292/15/18/4493

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