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
DSP-SLAM: Object Oriented SLAM with Deep Shape PriorsCode1
MAOMaps: A Photo-Realistic Benchmark For vSLAM and Map Merging Quality AssessmentCode1
Unsupervised Scale-consistent Depth Learning from VideoCode1
Real-time Multi-Adaptive-Resolution-Surfel 6D LiDAR Odometry using Continuous-time Trajectory OptimizationCode1
Graph-based Thermal-Inertial SLAM with Probabilistic Neural NetworksCode1
LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAMCode1
Sequential Place Learning: Heuristic-Free High-Performance Long-Term Place RecognitionCode1
OV^2SLAM : A Fully Online and Versatile Visual SLAM for Real-Time ApplicationsCode1
MULLS: Versatile LiDAR SLAM via Multi-metric Linear Least SquareCode1
GEM: Online Globally consistent dense elevation mapping for unstructured terrainCode1
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