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 91–100 of 572 papers

TitleStatusHype
Bayesian NeRF: Quantifying Uncertainty with Volume Density for Neural Implicit FieldsCode1
Fast and Incremental Loop Closure Detection with Deep Features and Proximity GraphsCode1
High-resolution Ecosystem Mapping in Repetitive Environments Using Dual Camera SLAMCode1
Optimal Target Shape for LiDAR Pose EstimationCode1
miniSAM: A Flexible Factor Graph Non-linear Least Squares Optimization FrameworkCode1
MULLS: Versatile LiDAR SLAM via Multi-metric Linear Least SquareCode1
CPL-SLAM: Efficient and Certifiably Correct Planar Graph-Based SLAM Using the Complex Number RepresentationCode1
Incremental Visual-Inertial 3D Mesh Generation with Structural RegularitiesCode1
Deep Keypoint-Based Camera Pose Estimation with Geometric ConstraintsCode1
Deep Depth Estimation from Visual-Inertial SLAMCode1
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