BayesianGS-SLAM: Uncertainty-Aware 3DGS SLAM Uses Bayesian Uncertainty Across Mapping, Tracking and Keyframes
zhenjun_zhao · x · 2026-09-22
- Researchers propose BayesianGS-SLAM, an uncertainty-aware 3D Gaussian Splatting SLAM framework posted on arXiv.
- Predictive uncertainty combines a sensor-noise component with an opacity-induced map-representation component propagated through rendering, covering both color and depth.
- The uncertainty is reused across the whole pipeline: augmenting mapping, normalizing tracking residuals via a robust pose objective, and selecting keyframes with a predictive-surprise criterion.
- Unlike prior work limited to color uncertainty or mapping-only use, the framework was validated on real-world RGB-D benchmarks.
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