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Point Cloud Registration

191 평가 기록 25 datasets

Point Cloud Registration is a fundamental problem in 3D computer vision and photogrammetry. Given several sets of points in different coordinate systems, the aim of registration is to find the transformation that best aligns all of them into a common coordinate system. Point Cloud Registration plays a significant role in many vision applications such as 3D model reconstruction, cultural heritage management, landslide monitoring and solar energy analysis.

<span class="description-source">Source: Iterative Global Similarity Points : A robust coarse-to-fine integration solution for pairwise 3D point cloud registration </span>

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Dataset기록된 모델 예시MetricPaperCode
GeDi
Feature Matching Recall: 0.982Recall (30cm, 5 degrees): 86.54
논문 코드
IMFNet
Feature Matching Recall: 98.6
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NgeNet
Recall (0.3m, 15 degrees): 95.0RE (all): 4.932TE (all): 0.155
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GeDi
Success Rate: 98.92
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CoFF
Recall ( correspondence RMSE below 0.2): 81.6
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NgeNet
Recall ( correspondence RMSE below 0.2): 92.9
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GeoTransformer
Recall (0.6m, 5 degrees): 99.5
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Greedy Grid Search
Recall (3cm, 10 degrees): 92.81RRE (degrees): 0.014RTE (cm): 0.009
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FPFH+SC2-PCR
Recall (3cm, 10 degrees): 99.88RRE (degrees): 0.91RTE (cm): 0.43
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FPFH+SC2-PCR
Recall (3cm, 10 degrees): 38.85RRE (degrees): 2.42RTE (cm): 1.23
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Exhaustive Grid Search
Recall (3cm, 10 degrees): 88.06RRE (degrees): 0.030RTE (cm): 0.017
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GeDi
Recall (3cm, 10 degrees): 99.76RRE (degrees): 1.629RTE (cm): 1.162
논문 코드

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