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The Alignment of the Spheres: Globally-Optimal Spherical Mixture Alignment for Camera Pose Estimation

CVPR 2019 · 3D vision › Human pose estimation · approach: Learned camera pose estimation · 40 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add semantic labels during optimization (ablation)GOSMA · Stanford 2D-3D-S area 3success rate: 0.85 -> 1.00Helped
add semantic labels during optimization (ablation)GOSMA · Stanford 2D-3D-S area 3median translation error (m): 0.14 -> 0.08Helped
add semantic labels during optimization (ablation)GOSMA · Stanford 2D-3D-S area 3median rotation error (°): 2.38 -> 1.13Helped
add semantic labels during optimization (ablation)GOSMA · Stanford 2D-3D-S area 3median runtime (s): 19.1 -> 1.8Helped
use GOSMA rather than GOPACcamera pose estimation · Synthetic data, ω₂D=1median runtime (s): 167s -> 5sHelped

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