Visual Place Recognition
81 papers with code • 14 benchmarks • 15 datasets
Visual Place Recognition is the task of matching a view of a place with a different view of the same place taken at a different time.
Source: Visual place recognition using landmark distribution descriptors
Image credit: Visual place recognition using landmark distribution descriptors
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LibrariesUse these libraries to find Visual Place Recognition models and implementations
Most implemented papers
SuperGlue: Learning Feature Matching with Graph Neural Networks
This paper introduces SuperGlue, a neural network that matches two sets of local features by jointly finding correspondences and rejecting non-matchable points.
NetVLAD: CNN architecture for weakly supervised place recognition
We tackle the problem of large scale visual place recognition, where the task is to quickly and accurately recognize the location of a given query photograph.
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition
This is largely due to the difficulty in extracting local feature descriptors from a point cloud that can subsequently be encoded into a global descriptor for the retrieval task.
Visual Localization Under Appearance Change: Filtering Approaches
Our approaches rely on local features with an encoding technique to represent an image as a single vector.
From Coarse to Fine: Robust Hierarchical Localization at Large Scale
In this paper we propose HF-Net, a hierarchical localization approach based on a monolithic CNN that simultaneously predicts local features and global descriptors for accurate 6-DoF localization.
Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
Visual Place Recognition is a challenging task for robotics and autonomous systems, which must deal with the twin problems of appearance and viewpoint change in an always changing world.
Real-Time Visual Place Recognition for Personal Localization on a Mobile Device
The paper presents an approach to indoor personal localization on a mobile device based on visual place recognition.
G2D: from GTA to Data
This document describes G2D, a software that enables capturing videos from Grand Theft Auto V (GTA V), a popular role playing game set in an expansive virtual city.
LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis
Point cloud based place recognition is still an open issue due to the difficulty in extracting local features from the raw 3D point cloud and generating the global descriptor, and it's even harder in the large-scale dynamic environments.
Adaptive-Attentive Geolocalization from few queries: a hybrid approach
We address the task of cross-domain visual place recognition, where the goal is to geolocalize a given query image against a labeled gallery, in the case where the query and the gallery belong to different visual domains.