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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 51–60 of 572 papers

TitleStatusHype
DXSLAM: A Robust and Efficient Visual SLAM System with Deep FeaturesCode1
LF-VISLAM: A SLAM Framework for Large Field-of-View Cameras with Negative Imaging Plane on Mobile AgentsCode1
EndoMapper dataset of complete calibrated endoscopy proceduresCode1
Embracing Dynamics: Dynamics-aware 4D Gaussian Splatting SLAMCode1
A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine IntelligenceCode1
LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAMCode1
Learning How To Robustly Estimate Camera Pose in Endoscopic VideosCode1
Fast and Incremental Loop Closure Detection Using Proximity GraphsCode1
D^3FlowSLAM: Self-Supervised Dynamic SLAM with Flow Motion Decomposition and DINO GuidanceCode1
HPointLoc: Point-based Indoor Place Recognition using Synthetic RGB-D ImagesCode1
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