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.
Neural refine- ment for absolute pose regression with feature synthesis
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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.