SplitGS-Loc disambiguates 2D-3D correspondences in photometrically optimized GSFFs via Mixture-of-Gaussians splitting and multi-view consistency selection, yielding stable PnP and SOTA localization results.
From coarse to fine: Robust hierarchical localization at large scale
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DINO features combined with many-to-many association and the proposed Harmonic Consensus Maximization enable general visual features to compete with specialized models on out-of-distribution image matching and camera pose estimation.
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Disambiguating 2D-3D Correspondences in Gaussian Splatting-based Feature Fields for Visual Localization
SplitGS-Loc disambiguates 2D-3D correspondences in photometrically optimized GSFFs via Mixture-of-Gaussians splitting and multi-view consistency selection, yielding stable PnP and SOTA localization results.
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Deploy DINO with Many-to-Many Association
DINO features combined with many-to-many association and the proposed Harmonic Consensus Maximization enable general visual features to compete with specialized models on out-of-distribution image matching and camera pose estimation.