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 291–300 of 572 papers

TitleStatusHype
Rotational Outlier Identification in Pose Graphs Using Dual Decomposition—0
Rotation Averaging: A Primal-Dual Method and Closed-Forms in Cycle Graphs—0
S3E-GNN: Sparse Spatial Scene Embedding with Graph Neural Networks for Camera Relocalization—0
S3-SLAM: Sparse Tri-plane Encoding for Neural Implicit SLAM—0
SafeNav: Safe Path Navigation using Landmark Based Localization in a GPS-denied Environment—0
Scaffold-SLAM: Structured 3D Gaussians for Simultaneous Localization and Photorealistic Mapping—0
Scalable Structure From Motion for Densely Sampled Videos—0
SD-6DoF-ICLK: Sparse and Deep Inverse Compositional Lucas-Kanade Algorithm on SE(3)—0
Seamless Augmented Reality Integration in Arthroscopy: A Pipeline for Articular Reconstruction and Guidance—0
Segway DRIVE Benchmark: Place Recognition and SLAM Data Collected by A Fleet of Delivery Robots—0
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