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 301–350 of 572 papers

TitleStatusHype
Automated Wheat Disease Detection using a ROS-based Autonomous Guided UAV—0
Automatic Impact-sounding Acoustic Inspection of Concrete Structure—0
Automatic Vocabulary and Graph Verification for Accurate Loop Closure Detection—0
Autonomous Asteroid Characterization Through Nanosatellite Swarming—0
Autonomous Navigation in Dynamic Environments: Deep Learning-Based Approach—0
A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM—0
Visual Perception System for Autonomous Driving—0
BAD SLAM: Bundle Adjusted Direct RGB-D SLAM—0
Batch SLAM with PMBM Data Association Sampling and Graph-Based Optimization—0
Bayesian Integration of Multi-resolutional Grid Codes for Spatial Cognition—0
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC—0
BirdSLAM: Monocular Multibody SLAM in Bird's-Eye View—0
Black-box Adversarial Attacks on CNN-based SLAM Algorithms—0
BlinkTrack: Feature Tracking over 100 FPS via Events and Images—0
BS3D: Building-scale 3D Reconstruction from RGB-D Images—0
Bundle Adjustment in the Eager Mode—0
Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect—0
CholecSeg8k: A Semantic Segmentation Dataset for Laparoscopic Cholecystectomy Based on Cholec80—0
CLAM: Coupled Localization and Mapping with Efficient Outlier Handling—0
Closing the Calibration Loop: An Inside-out-tracking Paradigm for Augmented Reality in Orthopedic Surgery—0
Closing the Loop: Graph Networks to Unify Semantic Objects and Visual Features for Multi-object Scenes—0
Compositional Scalable Object SLAM—0
Construction Inspection through Spatial Database—0
Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection—0
Cooperative mmWave PHD-SLAM with Moving Scatterers—0
CP-SLAM: Collaborative Neural Point-based SLAM System—0
CudaSIFT-SLAM: multiple-map visual SLAM for full procedure mapping in real human endoscopy—0
cuVSLAM: CUDA accelerated visual odometry and mapping—0
DARE-SLAM: Degeneracy-Aware and Resilient Loop Closing in Perceptually-Degraded Environments—0
Data Fusion for Multipath-Based SLAM: Combining Information from Multiple Propagation Paths—0
Data Fusion for Radio Frequency SLAM with Robust Sampling—0
Deep Learning-based Cooperative LiDAR Sensing for Improved Vehicle Positioning—0
Deep-Learning-Based Indoor Human Following of Mobile Robot Using Color Feature—0
Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications—0
Deep Learning for Visual Localization and Mapping: A Survey—0
Deep Learning Reforms Image Matching: A Survey and Outlook—0
DeepPointMap: Advancing LiDAR SLAM with Unified Neural Descriptors—0
DeepRelativeFusion: Dense Monocular SLAM using Single-Image Relative Depth Prediction—0
Deep Visual Odometry Methods for Mobile Robots—0
DeepVO: A Deep Learning approach for Monocular Visual Odometry—0
Degeneracy in Self-Calibration Revisited and a Deep Learning Solution for Uncalibrated SLAM—0
Degenerate Motions in Multicamera Cluster SLAM with Non-overlapping Fields of View—0
Dense monocular Simultaneous Localization and Mapping by direct surfel optimization—0
Dense Object Reconstruction from RGBD Images with Embedded Deep Shape Representations—0
Dense RGB SLAM with Neural Implicit Maps—0
Design, Implementation and Evaluation of an External Pose-Tracking System for Underwater Cameras—0
DF-SLAM: A Deep-Learning Enhanced Visual SLAM System based on Deep Local Features—0
Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation—0
Direction-Aware Semi-Dense SLAM—0
Direct Multipath-Based SLAM—0
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