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Deep Graph-Based Spatial Consistency for Robust Non-Rigid Point Cloud Registration

CVPR 2023 · Point clouds › Registration and matching · approach: Non-rigid point set registration · 41 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
apply GraphSCNet outlier pruning to Lepard correspondencesLepard · 4DMatchAccS: 54.2 -> 70.1Helped
apply GraphSCNet outlier pruning to Lepard correspondencesLepard · 4DLoMatchAccS: 17.4 -> 40.0Helped
apply GraphSCNet outlier pruning to GeoTransformer correspondencesGeoTransformer · 4DMatchAccS: 65.5 -> 72.3Helped
apply GraphSCNet outlier pruning to GeoTransformer correspondencesGeoTransformer · 4DLoMatchAccS: 31.4 -> 41.0Helped
use node coverage σn = 0.04 instead of 0.08 (ablation)GraphSCNet · 4DMatchAccS: 72.3 -> 70.6Hurt
increase node coverage to σn = 0.32 (ablation)GraphSCNet · 4DMatchAccS: 72.3 -> 69.5Hurt
replace furthest-point node sampling with random sampling (ablation)GraphSCNet · 4DMatchAccS: 72.3 -> 72.5No clear effect
use correspondence-centered kNN graph construction (ablation)GraphSCNet · 4DMatchAccS: 72.3 -> 71.9Hurt
assign correspondences to only one neighboring node (ablation)GraphSCNet · 4DMatchAccS: 72.3 -> 59.7Hurt
assign correspondences to nine neighboring nodes (ablation)GraphSCNet · 4DMatchAccS: 72.3 -> 69.8Hurt
replace Euclidean graph distance with geodesic distance (ablation)GraphSCNet · 4DMatchAccS: 72.3 -> 71.1Hurt
remove Fourier positional encoding (ablation)GraphSCNet · 4DMatchAccS: 72.3 -> 72.3No clear effect

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