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 411–420 of 572 papers

TitleStatusHype
Deep Depth Estimation from Visual-Inertial SLAMCode1
Online Visual Place Recognition via Saliency Re-identificationCode1
Deep Keypoint-Based Camera Pose Estimation with Geometric ConstraintsCode1
A SLAM Map Restoration Algorithm Based on Submaps and an Undirected Connected Graph—0
EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearnerCode1
Exploiting Diffuse Multipath in 5G SLAM—0
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
Revisiting visual-inertial structure from motion for odometry and SLAM initialization—0
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