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 551–572 of 572 papers

TitleStatusHype
View Selection with Geometric Uncertainty Modeling—0
Pop-up SLAM: Semantic Monocular Plane SLAM for Low-texture Environments—0
Augmented Reality for Depth Cues in Monocular Minimally Invasive Surgery—0
Monocular LSD-SLAM Integration within AR SystemCode0
Keyframe-Based Visual-Inertial Online SLAM with Relocalization—0
A Survey of Structure from Motion—0
DeepVO: A Deep Learning approach for Monocular Visual Odometry—0
Construction Inspection through Spatial Database—0
MultiCol-SLAM - A Modular Real-Time Multi-Camera SLAM SystemCode0
ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D CamerasCode1
Visual-Inertial Monocular SLAM with Map ReuseCode0
Spatiotemporal Articulated Models for Dynamic SLAM—0
Volume-based Semantic Labeling with Signed Distance Functions—0
Degenerate Motions in Multicamera Cluster SLAM with Non-overlapping Fields of View—0
Robust Large Scale Monocular Visual SLAM—0
Scalable Structure From Motion for Densely Sampled Videos—0
Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection—0
Appearance-based indoor localization: A comparison of patch descriptor performance—0
ORB-SLAM: a Versatile and Accurate Monocular SLAM SystemCode0
Simultaneous Localization, Mapping, and Manipulation for Unsupervised Object Discovery—0
LOAM: Lidar Odometry and Mapping in Real-TimeCode0
CLAM: Coupled Localization and Mapping with Efficient Outlier Handling—0
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