A public benchmark dataset and competition results for 3D dental landmark detection from intraoral scans, with the top team reaching 0.91 rank score using a stratified transformer and DBSCAN.
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3 Pith papers cite this work. Polarity classification is still indexing.
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A topology-constrained 8-bit quantized nnUNet with connected-component, adjacency, and hole penalties reduces topological errors in tooth segmentation compared to standard quantization.
Equivariant mesh networks with anatomical priors and augmented message passing deliver stable segmentation across edge, vertex, and face supervision while resisting geometric perturbations.
citing papers explorer
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Detecting Dental Landmarks from Intraoral 3D Scans: the 3DTeethLand challenge
A public benchmark dataset and competition results for 3D dental landmark detection from intraoral scans, with the top team reaching 0.91 rank score using a stratified transformer and DBSCAN.
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Topology-Constrained Quantized nnUNet for Efficient and Anatomically Accurate 3D Tooth Segmentation
A topology-constrained 8-bit quantized nnUNet with connected-component, adjacency, and hole penalties reduces topological errors in tooth segmentation compared to standard quantization.
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Augmented Equivariant Mesh Networks for Anatomical Segmentation
Equivariant mesh networks with anatomical priors and augmented message passing deliver stable segmentation across edge, vertex, and face supervision while resisting geometric perturbations.