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Point Cloud Registration On Kitti Trained On
Point Cloud Registration On Kitti Trained On
評価指標
Success Rate
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
Success Rate
Paper Title
Repository
FCGF+PointDSC
96.76
PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency
GeoTransformer
67.93
GeoTransformer: Fast and Robust Point Cloud Registration with Geometric Transformer
YOHO-O
81.44
You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors
GeDi
98.92
Learning general and distinctive 3D local deep descriptors for point cloud registration
FCGF
24.19
Fully Convolutional Geometric Features
YOHO-C
82.16
You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors
SpinNet
81.44
SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration
D3Feat-pred
36.76
D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
Greedy Grid Search
90.27
Challenging the Universal Representation of Deep Models for 3D Point Cloud Registration
FCGF+SC2-PCR
97.66
SC2-PCR: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration
-
Exhaustive Grid Search
94.95
Addressing the generalization of 3D registration methods with a featureless baseline and an unbiased benchmark
Predator
41.20
PREDATOR: Registration of 3D Point Clouds with Low Overlap
FPFH+PointDSC
94.05
PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency
DIP
93.51
Distinctive 3D local deep descriptors
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