The paper reformulates absolute pose regression as regressing disentangled world-coordinate raymaps and pointmaps from images, then recovering pose via a differentiable solver, claiming SOTA results on 7-Scenes and Cambridge Landmarks.
A solution for the best rotation to relate two sets of vectors.Foundations of Crystallography, 32(5): 922–923, 1976
2 Pith papers cite this work. Polarity classification is still indexing.
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GenMatter is a generative hierarchical model that groups low-level motion and high-level features into particles and clusters representing independently moveable physical entities, validated across dot kinematograms, camouflaged objects, and RGB videos.
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GRLoc: Geometric Representation Regression for Visual Localization
The paper reformulates absolute pose regression as regressing disentangled world-coordinate raymaps and pointmaps from images, then recovering pose via a differentiable solver, claiming SOTA results on 7-Scenes and Cambridge Landmarks.
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GenMatter: Perceiving Physical Objects with Generative Matter Models
GenMatter is a generative hierarchical model that groups low-level motion and high-level features into particles and clusters representing independently moveable physical entities, validated across dot kinematograms, camouflaged objects, and RGB videos.