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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 111–120 of 572 papers

TitleStatusHype
Online Visual Place Recognition via Saliency Re-identificationCode1
EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearnerCode1
CPL-SLAM: Efficient and Certifiably Correct Planar Graph-Based SLAM Using the Complex Number RepresentationCode1
GMMLoc: Structure Consistent Visual Localization with Gaussian Mixture ModelsCode1
A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine IntelligenceCode1
Persistent Map Saving for Visual Localization for Autonomous Vehicles: An ORB-SLAM ExtensionCode1
Robust Line Segments Matching via Graph Convolution NetworksCode1
Intensity Scan Context: Coding Intensity and Geometry Relations for Loop Closure DetectionCode1
Fast and Incremental Loop Closure Detection Using Proximity GraphsCode1
Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and MappingCode1
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