MaLCA: Point Cloud Registration with Mamba-Enhanced Features and Local Correspondence Augmentation

High-quality correspondences are critical to the accuracy and robustness of point cloud registration. Existing Transformer-based methods are fundamentally constrained by the quadratic computational complexity of self-attention, resulting in limited scalability. Moreover, conventional outlier removal...

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Bibliographic Details

Published in:	Algorithms
Main Authors:	Yuchen Huo, Longyun Zhang, Huijuan Guo, Jingyi Gong, Liqun Kuang, Xie Han, Fengguang Xiong
Format:	Article
Language:	English
Published:	MDPI AG 2026-05-01
Subjects:	point cloud registration state space model Mamba correspondence augmentation
Online Access:	https://www.mdpi.com/1999-4893/19/5/380