EdgeFormer converts point cloud edge detection into local-patch point classification with a transformer and reports competitive results against six baselines.
Fast and robust edge extraction in unorganized point clouds
2 Pith papers cite this work. Polarity classification is still indexing.
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RWoDSN extracts feature points from point clouds via a novel DSN descriptor and random walk graph analysis, reporting 22% higher recall than prior state-of-the-art with 0.784 precision.
citing papers explorer
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EdgeFormer: local patch-based edge detection transformer on point clouds
EdgeFormer converts point cloud edge detection into local-patch point classification with a transformer and reports competitive results against six baselines.
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Random Walk on Point Clouds for Feature Detection
RWoDSN extracts feature points from point clouds via a novel DSN descriptor and random walk graph analysis, reporting 22% higher recall than prior state-of-the-art with 0.784 precision.