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Local-consistent Transformation Learning for Rotation-invariant Point Cloud Analysis
March 19, 2024, 4:48 a.m. | Yiyang Chen, Lunhao Duan, Shanshan Zhao, Changxing Ding, Dacheng Tao
cs.CV updates on arXiv.org arxiv.org
Abstract: Rotation invariance is an important requirement for point shape analysis. To achieve this, current state-of-the-art methods attempt to construct the local rotation-invariant representation through learning or defining the local reference frame (LRF). Although efficient, these LRF-based methods suffer from perturbation of local geometric relations, resulting in suboptimal local rotation invariance. To alleviate this issue, we propose a Local-consistent Transformation (LocoTrans) learning strategy. Specifically, we first construct the local-consistent reference frame (LCRF) by considering the symmetry …
analysis arxiv cloud consistent cs.cv rotation transformation type
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