GeoGS-SLAM removes appearance parameters from 3D Gaussian Splatting for geometry-only dense monocular SLAM, achieving faster convergence and fewer primitives while introducing a coherent Sim(3) map update for loop closure.
Gs- slam: Dense visual slam with 3d gaussian splatting
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.RO 2years
2026 2representative citing papers
UfM* uses Gaussian mixtures to compute multiview disagreement for uncertainty in depth estimation with single inference per image, reducing energy and memory use.
citing papers explorer
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GeoGS-SLAM: Geometry-Only Gaussian Splatting for Dense Monocular SLAM
GeoGS-SLAM removes appearance parameters from 3D Gaussian Splatting for geometry-only dense monocular SLAM, achieving faster convergence and fewer primitives while introducing a coherent Sim(3) map update for loop closure.
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UfM*: Uncertainty from Motion* for DNN Depth Estimation Using Gaussians
UfM* uses Gaussian mixtures to compute multiview disagreement for uncertainty in depth estimation with single inference per image, reducing energy and memory use.