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Point Cloud Registration On Eth Trained On

المقاييس

Feature Matching Recall

النتائج

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اسم النموذج
Feature Matching Recall
Paper TitleRepository
CGF0.202Learning Compact Geometric Features-
DIP0.928Distinctive 3D local deep descriptors-
GeDi0.982Learning general and distinctive 3D local deep descriptors for point cloud registration-
FPFH0.221Fast Point Feature Histograms (FPFH) for 3D Registration
FCGF0.161Fully Convolutional Geometric Features
D3Feat-pred0.563D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features-
PerfectMatch0.790The Perfect Match: 3D Point Cloud Matching with Smoothed Densities-
Greedy Grid Search0.784Challenging the Universal Representation of Deep Models for 3D Point Cloud Registration-
3DMatch0.1693DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions-
Exhaustive Grid Search-Addressing the generalization of 3D registration methods with a featureless baseline and an unbiased benchmark
FCGF+SC2-PCR-SC2-PCR: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration-
YOHO-O-You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors-
FPFH+PointDSC-PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency-
FPFH+SC2-PCR-SC2-PCR: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration-
GeoTransformer-GeoTransformer: Fast and Robust Point Cloud Registration with Geometric Transformer-
LMVD0.616End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds-
FCGF+PointDSC-PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency-
YOHO-C-You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors-
GO-ICP-Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration-
SpinNet0.928SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration-
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