place-recognition

LiDAR SLAM: Scan Context + LeGO-LOAM

A general framework for map-based visual localization. It contains 1) Map Generation which support traditional features or deeplearning features. 2) Hierarchical-Localizationvisual in visual(points or line) map. 3)Fusion framework with IMU, wheel odom and GPS sensors.

LiDAR-inertial SLAM: Scan Context + LIO-SAM

Code for the CVPR2021 paper "Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition"

ICRA 2021 - Robust Place Recognition using an Imaging Lidar

PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018

Robust LiDAR SLAM with a versatile plug-and-play loop closing and pose-graph optimization.

LiDAR SLAM = FAST-LIO + Scan Context

Place recognition with WiFi fingerprints using Autoencoders and Neural Networks

[ECCV-2020 (spotlight)] Self-supervising Fine-grained Region Similarities for Large-scale Image Localization. 🌏 PyTorch open-source toolbox for image-based localization (place recognition).

A 3D point cloud descriptor for place recognition

Convolutional Autoencoder for Loop Closure

Intelligent place recognition module for vins-fusion

Official code for CVPR 2022 paper "Rethinking Visual Geo-localization for Large-Scale Applications"

This repository contains the code implementation used in the paper "Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling". ICRA 2021.

MinkLoc3D: Point Cloud Based Large-Scale Place Recognition

Radar SLAM: yeti radar odometry + scan context

The Official Deep Learning Framework for Robot Place Learning

LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis, ICCV 2019, Seoul, Korea

Official code for CVPR 2022 (Oral) paper "Deep Visual Geo-localization Benchmark"