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 376–400 of 572 papers

TitleStatusHype
Autonomous Navigation in Dynamic Environments: Deep Learning-Based Approach—0
Anchor Distance for 3D Multi-Object Distance Estimation from 2D Single Shot—0
A Hybrid Learner for Simultaneous Localization and Mapping—0
CholecSeg8k: A Semantic Segmentation Dataset for Laparoscopic Cholecystectomy Based on Cholec80—0
GEM: Online Globally consistent dense elevation mapping for unstructured terrainCode1
Self-Supervised Learning of Lidar Segmentation for Autonomous Indoor NavigationCode1
Visual place recognition: A survey from deep learning perspectiveCode1
RISE-SLAM: A Resource-aware Inverse Schmidt Estimator for SLAM—0
Landmark and IMU Data Fusion: Systematic Convergence Geometric Nonlinear Observer for SLAM and Velocity Bias—0
Semantic SLAM with Autonomous Object-Level Data Association—0
DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place RecognitionCode1
BirdSLAM: Monocular Multibody SLAM in Bird's-Eye View—0
Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications—0
Kimera-Multi: a System for Distributed Multi-Robot Metric-Semantic Simultaneous Localization and Mapping—0
Online Descriptor Enhancement via Self-Labelling Triplets for Visual Data Association—0
Compositional Scalable Object SLAM—0
Pushing the Envelope of Rotation Averaging for Visual SLAM—0
Robust Odometry and Mapping for Multi-LiDAR Systems with Online Extrinsic CalibrationCode1
The RobotSlang Benchmark: Dialog-guided Robot Localization and Navigation—0
Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale EnvironmentCode1
A Two-stage Unsupervised Approach for Low light Image Enhancement—0
Homography Estimation with Convolutional Neural Networks Under Conditions of Variance—0
InpaintFusion: Incremental RGB-D Inpainting for 3D Scenes—0
Fast and Incremental Loop Closure Detection with Deep Features and Proximity GraphsCode1
Fast Adaptation Nonlinear Observer for SLAM—0
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