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 501–510 of 572 papers

TitleStatusHype
CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth PredictionCode0
Real-Time Monocular Object-Model Aware Sparse SLAM—0
Simultaneous Localization and Layout Model Selection in Manhattan Worlds—0
Monocular Object and Plane SLAM in Structured Environments—0
InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Dataset—0
A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM—0
Simultaneous Localization And Mapping with depth Prediction using Capsule Networks for UAVs—0
Deep Visual Odometry Methods for Mobile Robots—0
Towards an Embodied Semantic Fovea: Semantic 3D scene reconstruction from ego-centric eye-tracker videos—0
Loosely-Coupled Semi-Direct Monocular SLAMCode1
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