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الرئيسية
SOTA
تسجيل السحابة النقطية
Point Cloud Registration On 3Dmatch Benchmark
Point Cloud Registration On 3Dmatch Benchmark
المقاييس
Feature Matching Recall
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Feature Matching Recall
Paper Title
Repository
D3Feat-Pred
95.8
D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
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3DSmoothNet
94.7
The Perfect Match: 3D Point Cloud Matching with Smoothed Densities
-
PPF-FoldNet
71.8
PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors
-
D3Feat-rand
95.3
D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
-
IMFNet
98.6
IMFNet: Interpretable Multimodal Fusion for Point Cloud Registration
-
FCGF + RANSAC
85
Fully Convolutional Geometric Features
MS-SVConv
98.4
3D Point Cloud Registration with Multi-Scale Architecture and Unsupervised Transfer Learning
-
DIP
94.8
Distinctive 3D local deep descriptors
-
FPFH + RANSAC
44.2
Fast Point Feature Histograms (FPFH) for 3D Registration
SpinNet (no code published as of Dec 15 2020)
97.6
SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration
-
3DMatch + RANSAC
66.8
3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions
-
GeDi (no code published as of May 27 2021)
97.9
Learning general and distinctive 3D local deep descriptors for point cloud registration
-
DIP + Point-TnT
96.8
Points to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition
-
LMVD
97.5
End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds
-
PPFNet
62.3
PPFNet: Global Context Aware Local Features for Robust 3D Point Matching
-
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