VBGS-SLAM uses variational inference on conjugate Gaussian properties to couple 3DGS map refinement and pose tracking with closed-form updates and posterior uncertainty, reducing drift compared to deterministic methods.
A multi-state constraint kalman filter for vision-aided inertial navigation
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MUSE applies Mamba sequential modeling to produce real-time uncertainty estimates for visual-inertial state estimation from asynchronous multimodal sensors.
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VBGS-SLAM: Variational Bayesian Gaussian Splatting Simultaneous Localization and Mapping
VBGS-SLAM uses variational inference on conjugate Gaussian properties to couple 3DGS map refinement and pose tracking with closed-form updates and posterior uncertainty, reducing drift compared to deterministic methods.
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MUSE: Multimodal Uncertainty Quantification of State Estimation
MUSE applies Mamba sequential modeling to produce real-time uncertainty estimates for visual-inertial state estimation from asynchronous multimodal sensors.