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Loop Closure Detection

Loop closure detection is the process of detecting whether an agent has returned to a previously visited location.

( Image credit: Backtracking Regression Forests for Accurate Camera Relocalization )

Papers

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Showing 1–25 of 89 papers

TitleStatusHype
GV-Bench: Benchmarking Local Feature Matching for Geometric Verification of Long-term Loop Closure DetectionCode2
Contour Context: Abstract Structural Distribution for 3D LiDAR Loop Detection and Metric Pose EstimationCode2
OverlapMamba: Novel Shift State Space Model for LiDAR-based Place RecognitionCode2
DXSLAM: A Robust and Efficient Visual SLAM System with Deep FeaturesCode1
Place Recognition in Forests with Urquhart TessellationsCode1
Why Sample Space Matters: Keyframe Sampling Optimization for LiDAR-based Place RecognitionCode1
Loop closure detection using local 3D deep descriptorsCode1
Fast and Incremental Loop Closure Detection with Deep Features and Proximity GraphsCode1
Intensity Scan Context: Coding Intensity and Geometry Relations for Loop Closure DetectionCode1
Loop Closure Detection Based on Object-level Spatial Layout and Semantic ConsistencyCode1
On the descriptive power of LiDAR intensity images for segment-based loop closing in 3-D SLAMCode1
Phase-SLAM: Phase Based Simultaneous Localization and Mapping for Mobile Structured Light Illumination SystemsCode1
Probabilistic Appearance-Invariant Topometric Localization with New Place AwarenessCode1
Visual place recognition: A survey from deep learning perspectiveCode1
Balancing Accuracy and Efficiency for Large-Scale SLAM: A Minimal Subset Approach for Scalable Loop ClosuresCode1
Dynamic Object Tracking and Masking for Visual SLAMCode1
Fast and Incremental Loop Closure Detection Using Proximity GraphsCode1
CT-ICP: Real-time Elastic LiDAR Odometry with Loop ClosureCode1
General Place Recognition Survey: Towards the Real-world Autonomy AgeCode1
ForestLPR: LiDAR Place Recognition in Forests Attentioning Multiple BEV Density ImagesCode1
LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAMCode1
LiDAR Loop Closure Detection using Semantic Graphs with Graph Attention NetworksCode1
NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform RepresentationCode1
Closing the Loop: Graph Networks to Unify Semantic Objects and Visual Features for Multi-object Scenes—0
Bi-directional Loop Closure for Visual SLAM—0
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