Loop Closure Detection Edit Task
Computer Vision • Autonomous Vehicles
About
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 )
Benchmarks
Datasets
Greatest papers with code
Intensity Scan Context: Coding Intensity and Geometry Relations for Loop Closure Detection
Loop closure detection is an essential and challenging problem in simultaneous localization and mapping (SLAM).
LOOP CLOSURE DETECTION SIMULTANEOUS LOCALIZATION AND MAPPING
DXSLAM: A Robust and Efficient Visual SLAM System with Deep Features
For visual SLAM algorithms, though the theoretical framework has been well established for most aspects, feature extraction and association is still empirically designed in most cases, and can be vulnerable in complex environments.
LOOP CLOSURE DETECTION SIMULTANEOUS LOCALIZATION AND MAPPING
Fast and Incremental Loop Closure Detection with Deep Features and Proximity Graphs
In recent years, methods concerning the place recognition task have been extensively examined from the robotics community within the scope of simultaneous localization and mapping applications.
LOOP CLOSURE DETECTION SIMULTANEOUS LOCALIZATION AND MAPPING
Fast and Incremental Loop Closure Detection Using Proximity Graphs
Visual loop closure detection, which can be considered as an image retrieval task, is an important problem in SLAM (Simultaneous Localization and Mapping) systems.
IMAGE RETRIEVAL LOOP CLOSURE DETECTION SIMULTANEOUS LOCALIZATION AND MAPPING
Kernel learning for visual perception
To this end, the novel kernel learning methods for several basic visual perceptual tasks, including object tracking, localization, mapping, and image recognition, are proposed and demonstrated both theoretically and practically.
ACTIVITY RECOGNITION LOOP CLOSURE DETECTION OBJECT DETECTION OPTICAL FLOW ESTIMATION ROBOT NAVIGATION SIMULTANEOUS LOCALIZATION AND MAPPING TRANSFER LEARNING VISUAL OBJECT TRACKING VISUAL TRACKING
NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation
• dachengxiaocheng/NDT-Transformer
• 
Benefiting from the NDT representation and NDT-Transformer network, the learned global descriptors are enriched with both geometrical and contextual information.
Visual place recognition: A survey from deep learning perspective
Visual place recognition has attracted widespread research interest in multiple fields such as computer vision and robotics.
LOOP CLOSURE DETECTION SCENE UNDERSTANDING SIMULTANEOUS LOCALIZATION AND MAPPING VISUAL LOCALIZATION VISUAL PLACE RECOGNITION
Backtracking Regression Forests for Accurate Camera Relocalization
Camera relocalization plays a vital role in many robotics and computer vision tasks, such as global localization, recovery from tracking failure, and loop closure detection.
CAMERA RELOCALIZATION LOOP CLOSURE DETECTION SIMULTANEOUS LOCALIZATION AND MAPPING
Sem-LSD: A Learning-based Semantic Line Segment Detector
Combined with high-level semantics, Sem-LS is more robust under cluttered environment compared with existing line-shaped representations.
Place Recognition in Forests with Urquhart Tessellations
In this letter, we present a novel descriptor based on Urquhart tessellations derived from the position of trees in a forest.