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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

Showing 351375 of 572 papers

TitleStatusHype
Fisheye Lens Camera based Autonomous Valet Parking System0
Self-optimizing loop sifting and majorization for 3D reconstruction0
Real-time dense 3D Reconstruction from monocular video data captured by low-cost UAVs0
Graph-based Thermal-Inertial SLAM with Probabilistic Neural NetworksCode1
A Front-End for Dense Monocular SLAM using a Learned Outlier Mask Prior0
A comparative evaluation of learned feature descriptors on hybrid monocular visual SLAM methods0
A Novel Deep ML Architecture by Integrating Visual Simultaneous Localization and Mapping (vSLAM) into Mask R-CNN for Real-time Surgical Video Analysis0
LIFT-SLAM: a deep-learning feature-based monocular visual SLAM method0
SD-6DoF-ICLK: Sparse and Deep Inverse Compositional Lucas-Kanade Algorithm on SE(3)0
Multipath-based SLAM using Belief Propagation with Interacting Multiple Dynamic Models0
Map completion from partial observation using the global structure of multiple environmental maps0
GRIHA: Synthesizing 2-Dimensional Building Layouts from Images Captured using a Smart Phone0
Hippocampal formation-inspired probabilistic generative model0
Multiview Sensing With Unknown Permutations: An Optimal Transport Approach0
Real-time Nonrigid Mosaicking of Laparoscopy Images0
LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAMCode1
Advances in Inference and Representation for Simultaneous Localization and Mapping0
Sequential Place Learning: Heuristic-Free High-Performance Long-Term Place RecognitionCode1
Panoramic annular SLAM with loop closure and global optimization0
A Geometric Nonlinear Stochastic Filter for Simultaneous Localization and Mapping0
DARE-SLAM: Degeneracy-Aware and Resilient Loop Closing in Perceptually-Degraded Environments0
Learned Camera Gain and Exposure Control for Improved Visual Feature Detection and Matching0
OV^2SLAM : A Fully Online and Versatile Visual SLAM for Real-Time ApplicationsCode1
MULLS: Versatile LiDAR SLAM via Multi-metric Linear Least SquareCode1
A Collaborative Visual SLAM Framework for Service Robots0
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