Examines point cloud registration performance, highlighting challenges in low-overlap and large-scale scenarios.
Point Cloud Registration (PCR) is a basic task in computer vision, mobile robotics, and autonomous driving. PCR primarily faces challenges, including insufficient registration performance in low-overlap scenarios and high computational resource consumption in large-scale point cloud scenarios. Most recent PCR methods are transformer-based. Methods like transformers have quadratic computational complexity
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Cao et al. (2026) studied this question.
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