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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 121–130 of 572 papers

TitleStatusHype
ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D CamerasCode1
OV^2SLAM : A Fully Online and Versatile Visual SLAM for Real-Time ApplicationsCode1
Autonomous Navigation System from Simultaneous Localization and MappingCode1
Phase-SLAM: Phase Based Simultaneous Localization and Mapping for Mobile Structured Light Illumination SystemsCode1
Persistent Map Saving for Visual Localization for Autonomous Vehicles: An ORB-SLAM ExtensionCode1
Unsupervised Scale-consistent Depth Learning from VideoCode1
EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearnerCode1
QueensCAMP: an RGB-D dataset for robust Visual SLAMCode1
PanoSLAM: Panoptic 3D Scene Reconstruction via Gaussian SLAMCode0
Descriptellation: Deep Learned Constellation DescriptorsCode0
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