Point Cloud Registration On Eth Trained On

Feature Matching Recall

평가 결과

이 벤치마크에서 각 모델의 성능 결과

비교 표

모델 이름	Feature Matching Recall
learning-compact-geometric-features	0.202
distinctive-3d-local-deep-descriptors	0.928
generalisable-and-distinctive-3d-local-deep	0.982
fast-point-feature-histograms-fpfh-for-3d	0.221
fully-convolutional-geometric-features	0.161
d3feat-joint-learning-of-dense-detection-and	0.563
the-perfect-match-3d-point-cloud-matching	0.790
challenging-the-universal-representation-of	0.784
3dmatch-learning-local-geometric-descriptors	0.169
addressing-the-generalization-of-3d	-
sc2-pcr-a-second-order-spatial-compatibility	-
you-only-hypothesize-once-point-cloud	-
pointdsc-robust-point-cloud-registration	-
sc2-pcr-a-second-order-spatial-compatibility	-
geotransformer-fast-and-robust-point-cloud	-
end-to-end-learning-local-multi-view	0.616
pointdsc-robust-point-cloud-registration	-
you-only-hypothesize-once-point-cloud	-
go-icp-a-globally-optimal-solution-to-3d-icp	-
spinnet-learning-a-general-surface-descriptor	0.928