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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 71–80 of 89 papers

TitleStatusHype
Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection—0
DARE-SLAM: Degeneracy-Aware and Resilient Loop Closing in Perceptually-Degraded Environments—0
DDN-SLAM: Real-time Dense Dynamic Neural Implicit SLAM—0
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition—0
DK-SLAM: Monocular Visual SLAM with Deep Keypoint Learning, Tracking and Loop-Closing—0
DSC: Deep Scan Context Descriptor for Large-Scale Place Recognition—0
Exploiting Points and Lines in Regression Forests for RGB-D Camera Relocalization—0
Exploring Emerging Trends and Research Opportunities in Visual Place Recognition—0
Fast Loop Closure Detection via Binary Content—0
Fusing Event-based Camera and Radar for SLAM Using Spiking Neural Networks with Continual STDP Learning—0
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