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Simultaneous Localization and Mapping

Simultaneous localization and mapping (SLAM) is the task of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.

( Image credit: ORB-SLAM2 )

Papers

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Showing 51–60 of 572 papers

TitleStatusHype
Multicam-SLAM: Non-overlapping Multi-camera SLAM for Indirect Visual Localization and NavigationCode1
CoPeD-Advancing Multi-Robot Collaborative Perception: A Comprehensive Dataset in Real-World EnvironmentsCode1
Bayesian NeRF: Quantifying Uncertainty with Volume Density for Neural Implicit FieldsCode1
Gaussian Pancakes: Geometrically-Regularized 3D Gaussian Splatting for Realistic Endoscopic ReconstructionCode1
Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture EnvironmentsCode1
SemanticSLAM: Learning based Semantic Map Construction and Robust Camera LocalizationCode1
BDIS-SLAM: A lightweight CPU-based dense stereo SLAM for surgeryCode1
Continuous Pose for Monocular Cameras in Neural Implicit RepresentationCode1
Monocular visual simultaneous localization and mapping:(r) evolution from geometry to deep learning-based pipelinesCode1
DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance FieldsCode1
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