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 141–150 of 572 papers

TitleStatusHype
Anchor Distance for 3D Multi-Object Distance Estimation from 2D Single Shot—0
DeepVO: A Deep Learning approach for Monocular Visual Odometry—0
Automatic Vocabulary and Graph Verification for Accurate Loop Closure Detection—0
Deep Visual Odometry Methods for Mobile Robots—0
Automatic Impact-sounding Acoustic Inspection of Concrete Structure—0
A Hybrid Learner for Simultaneous Localization and Mapping—0
DeepRelativeFusion: Dense Monocular SLAM using Single-Image Relative Depth Prediction—0
DeepPointMap: Advancing LiDAR SLAM with Unified Neural Descriptors—0
Automated Wheat Disease Detection using a ROS-based Autonomous Guided UAV—0
Deep Learning Reforms Image Matching: A Survey and Outlook—0
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