SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–89 of 89 papers

TitleStatusHype
Beyond SIFT using Binary features for Loop Closure Detection—0
Bi-directional Loop Closure for Visual SLAM—0
Closing the Loop: Graph Networks to Unify Semantic Objects and Visual Features for Multi-object Scenes—0
Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection—0
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
Fusion++: Volumetric Object-Level SLAM—0
SeqLPD: Sequence Matching Enhanced Loop-Closure Detection Based on Large-Scale Point Cloud Description for Self-Driving Vehicles—0
LSGDDN-LCD: An Appearance-based Loop Closure Detection using Local Superpixel Grid Descriptors and Incremental Dynamic Nodes—0
Simultaneous Localization and Mapping Using Active mmWave Sensing in 5G NR—0
SLAM in the Dark: Self-Supervised Learning of Pose, Depth and Loop-Closure from Thermal Images—0
SymbioLCD: Ensemble-Based Loop Closure Detection using CNN-Extracted Objects and Visual Bag-of-Words—0
TReR: A Lightweight Transformer Re-Ranking Approach for 3D LiDAR Place Recognition—0
VINGS-Mono: Visual-Inertial Gaussian Splatting Monocular SLAM in Large Scenes—0
Visual Loop Closure Detection Through Deep Graph Consensus—0
Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry—0
Place recognition in gardens by learning visual representations: data set and benchmark analysis—0
PLD-SLAM: A Real-Time Visual SLAM Using Points and Line Segments in Dynamic Scenes—0
PNE-SGAN: Probabilistic NDT-Enhanced Semantic Graph Attention Network for LiDAR Loop Closure Detection—0
Pose Graph Optimization for Unsupervised Monocular Visual Odometry—0
RadarLCD: Learnable Radar-based Loop Closure Detection Pipeline—0
SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure—0
Semi-supervised Vector-Quantization in Visual SLAM using HGCN—0
ORCHNet: A Robust Global Feature Aggregation approach for 3D LiDAR-based Place recognition in OrchardsCode0
Backtracking Regression Forests for Accurate Camera RelocalizationCode0
Sem-LSD: A Learning-based Semantic Line Segment DetectorCode0
Kernel learning for visual perceptionCode0
AirLoop: Lifelong Loop Closure DetectionCode0
Region Prediction for Efficient Robot Localization on Large MapsCode0
Why-So-Deep: Towards Boosting Previously Trained Models for Visual Place RecognitionCode0
AttDLNet: Attention-based DL Network for 3D LiDAR Place RecognitionCode0
Show:102550
← PrevPage 2 of 2Next →

No leaderboard results yet.