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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 71–80 of 572 papers

TitleStatusHype
MBA-SLAM: Motion Blur Aware Dense Visual SLAM with Radiance Fields RepresentationCode2
LCP-Fusion: A Neural Implicit SLAM with Enhanced Local Constraints and Computable PriorCode1
LGU-SLAM: Learnable Gaussian Uncertainty Matching with Deformable Correlation Sampling for Deep Visual SLAMCode1
NYC-Event-VPR: A Large-Scale High-Resolution Event-Based Visual Place Recognition Dataset in Dense Urban EnvironmentsCode1
QueensCAMP: an RGB-D dataset for robust Visual SLAMCode1
V3D-SLAM: Robust RGB-D SLAM in Dynamic Environments with 3D Semantic Geometry VotingCode1
ESVO2: Direct Visual-Inertial Odometry with Stereo Event CamerasCode2
An Expeditious Spatial Mean Radiant Temperature Mapping Framework using Visual SLAM and Semantic Segmentation—0
EvenNICER-SLAM: Event-based Neural Implicit Encoding SLAM—0
Seamless Augmented Reality Integration in Arthroscopy: A Pipeline for Articular Reconstruction and Guidance—0
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