SOTAVerified

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 41–50 of 572 papers

TitleStatusHype
General Place Recognition Survey: Towards the Real-world Autonomy AgeCode1
Gaussian Pancakes: Geometrically-Regularized 3D Gaussian Splatting for Realistic Endoscopic ReconstructionCode1
GEM: Online Globally consistent dense elevation mapping for unstructured terrainCode1
FLSea: Underwater Visual-Inertial and Stereo-Vision Forward-Looking DatasetsCode1
Fast and Incremental Loop Closure Detection with Deep Features and Proximity GraphsCode1
A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine IntelligenceCode1
High-resolution Ecosystem Mapping in Repetitive Environments Using Dual Camera SLAMCode1
Embracing Dynamics: Dynamics-aware 4D Gaussian Splatting SLAMCode1
ATDN vSLAM: An all-through Deep Learning-Based Solution for Visual Simultaneous Localization and MappingCode1
DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance FieldsCode1
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