GaussianFlow SLAM aligns projected Gaussian motion with optical flow to regularize monocular 3D Gaussian splatting SLAM, yielding better map quality and pose accuracy than prior methods.
Dgs-slam: Gaussian splatting slam in dynamic environment
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 5verdicts
UNVERDICTED 5roles
background 1polarities
background 1representative citing papers
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.
MoPe propagates historical dynamic posteriors via SE(3) warping and bounded Bayesian fusion to maintain persistent motion state in monocular Gaussian SLAM.
CubifyGS introduces object-level asset management in 3D Gaussian Splatting to handle object rearrangements in lifelong dynamic scenes more efficiently than primitive-level updates.
Flow4DGS-SLAM uses optical flow to generate motion masks, initialize poses, and guide 4D Gaussian modeling with scene flow and GMM for temporal properties, claiming SOTA results in dynamic tracking and reconstruction.
citing papers explorer
-
GaussianFlow SLAM: Monocular Gaussian Splatting SLAM Guided by GaussianFlow
GaussianFlow SLAM aligns projected Gaussian motion with optical flow to regularize monocular 3D Gaussian splatting SLAM, yielding better map quality and pose accuracy than prior methods.
-
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.
-
MoPe: Motion Permanence for Robust Monocular Gaussian Mapping in Dynamic Environments
MoPe propagates historical dynamic posteriors via SE(3) warping and bounded Bayesian fusion to maintain persistent motion state in monocular Gaussian SLAM.
-
CubifyGS: Object-Centric 3D Gaussian Splatting for Lifelong Dynamic Scene Maintenance
CubifyGS introduces object-level asset management in 3D Gaussian Splatting to handle object rearrangements in lifelong dynamic scenes more efficiently than primitive-level updates.
-
Flow4DGS-SLAM: Optical Flow-Guided 4D Gaussian Splatting SLAM
Flow4DGS-SLAM uses optical flow to generate motion masks, initialize poses, and guide 4D Gaussian modeling with scene flow and GMM for temporal properties, claiming SOTA results in dynamic tracking and reconstruction.