Visual Place Recognition
100 papers with code • 27 benchmarks • 19 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
Libraries
Use these libraries to find Visual Place Recognition models and implementationsDatasets
Most implemented papers
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.
Rethinking Visual Geo-localization for Large-Scale Applications
Visual Geo-localization (VG) is the task of estimating the position where a given photo was taken by comparing it with a large database of images of known locations.
Efficient Decentralized Visual Place Recognition From Full-Image Descriptors
As we show, casting this to a key-value lookup problem can be achieved with k-means clustering, and results in a much simpler system than [1].
HBST: A Hamming Distance embedding Binary Search Tree for Visual Place Recognition
Reliable and efficient Visual Place Recognition is a major building block of modern SLAM systems.
LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics
Human visual scene understanding is so remarkable that we are able to recognize a revisited place when entering it from the opposite direction it was first visited, even in the presence of extreme variations in appearance.
Adding Cues to Binary Feature Descriptors for Visual Place Recognition
In this paper we propose an approach to embed continuous and selector cues in binary feature descriptors used for visual place recognition.
Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space
In this paper we present an end-to-end deep learning framework to turn images that show dynamic content, such as vehicles or pedestrians, into realistic static frames.
Large scale visual place recognition with sub-linear storage growth
Robotic and animal mapping systems share many of the same objectives and challenges, but differ in one key aspect: where much of the research in robotic mapping has focused on solving the data association problem, the grid cell neurons underlying maps in the mammalian brain appear to intentionally break data association by encoding many locations with a single grid cell neuron.