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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 91–100 of 572 papers

TitleStatusHype
Event-based Simultaneous Localization and Mapping: A Comprehensive SurveyCode1
Continuous Pose for Monocular Cameras in Neural Implicit RepresentationCode1
Bayesian NeRF: Quantifying Uncertainty with Volume Density for Neural Implicit FieldsCode1
EndoMapper dataset of complete calibrated endoscopy proceduresCode1
DXSLAM: A Robust and Efficient Visual SLAM System with Deep FeaturesCode1
DSP-SLAM: Object Oriented SLAM with Deep Shape PriorsCode1
CPL-SLAM: Efficient and Certifiably Correct Planar Graph-Based SLAM Using the Complex Number RepresentationCode1
Multicam-SLAM: Non-overlapping Multi-camera SLAM for Indirect Visual Localization and NavigationCode1
DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance FieldsCode1
DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place RecognitionCode1
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