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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 181–190 of 572 papers

TitleStatusHype
Inertial Guided Uncertainty Estimation of Feature Correspondence in Visual-Inertial Odometry/SLAM—0
Resilient Simultaneous Localization and Mapping Fusing Ultra Wide Band Range Measurements and Visual Odometry—0
TivNe-SLAM: Dynamic Mapping and Tracking via Time-Varying Neural Radiance Fields—0
Towards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos using NeRFs—0
Learning Neural Implicit through Volume Rendering with Attentive Depth Fusion Priors—0
Jointly Optimized Global-Local Visual Localization of UAVs—0
3DS-SLAM: A 3D Object Detection based Semantic SLAM towards Dynamic Indoor Environments—0
HI-SLAM: Monocular Real-time Dense Mapping with Hybrid Implicit Fields—0
Monocular visual simultaneous localization and mapping:(r) evolution from geometry to deep learning-based pipelinesCode1
Language-EXtended Indoor SLAM (LEXIS): A Versatile System for Real-time Visual Scene Understanding—0
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