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Deep Global Registration

CVPR 2020 · 3D vision › Human pose estimation · approach: Learned camera pose estimation · 559 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use Deep Global Registration instead of RANSAC-8M3DMatch pairwise registration · 3DMatch testrecall: 74.9% -> 91.3%Helped
use Deep Global Registration instead of RANSAC-8M3DMatch pairwise registration · 3DMatch testTE (cm): 8.96 -> 7.34Helped
use Deep Global Registration instead of RANSAC-8M3DMatch pairwise registration · 3DMatch testRE (deg): 2.92 -> 2.43Helped
remove safeguard registration (ablation)Deep Global Registration · 3DMatch testrecall: 85.2% -> 91.3%Hurt
remove safeguard registration (ablation)Deep Global Registration · 3DMatch testTE (cm): 7.34 -> 7.73Hurt
remove safeguard registration (ablation)Deep Global Registration · 3DMatch testRE (deg): 2.43 -> 2.58Hurt
add ICP fine-grained pose adjustment (ablation)Deep Global Registration · KITTI test splitTE (cm): 21.7 -> 3.46Helped
add ICP fine-grained pose adjustment (ablation)Deep Global Registration · KITTI test splitrecall: 96.9% -> 98.0%Helped
add ICP fine-grained pose adjustment (ablation)Deep Global Registration · KITTI test splitRE (deg): 0.34 -> 0.14Helped
use multi-way registration with the proposed pairwise method rather than the tested alternativesAugmented ICL-NUIM reconstruction · Augmented ICL-NUIMAvg. Rank: 2.5 -> 2Helped

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