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 141–150 of 572 papers

TitleStatusHype
Neural SLAM: Learning to Explore with External MemoryCode0
Visual-Inertial SLAM for Unstructured Outdoor Environments: Benchmarking the Benefits and Computational Costs of Loop ClosingCode0
MultiCol-SLAM - A Modular Real-Time Multi-Camera SLAM SystemCode0
CorrAdaptor: Adaptive Local Context Learning for Correspondence PruningCode0
Not Only Look But Observe: Variational Observation Model of Scene-Level 3D Multi-Object Understanding for Probabilistic SLAMCode0
PanoSLAM: Panoptic 3D Scene Reconstruction via Gaussian SLAMCode0
Monocular LSD-SLAM Integration within AR SystemCode0
Continuous Direct Sparse Visual Odometry from RGB-D ImagesCode0
Co-Fusion: Real-time Segmentation, Tracking and Fusion of Multiple ObjectsCode0
CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth PredictionCode0
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