Visual Place Recognition
136 papers with code • 36 benchmarks • 24 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
Benchmarks
These leaderboards are used to track progress in Visual Place Recognition
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Libraries
Use these libraries to find Visual Place Recognition models and implementationsDatasets
KITTI
NCLT
Mapillary Vistas Dataset
MSLS
DDD17
Oxford RobotCar Dataset
GSV-Cities
Nordland
AmsterTime
Most implemented papers
Emerging Properties in Self-Supervised Vision Transformers
facebookresearch/dino
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ICCV 2021
In this paper, we question if self-supervised learning provides new properties to Vision Transformer (ViT) that stand out compared to convolutional networks (convnets).
DINOv2: Learning Robust Visual Features without Supervision
The recent breakthroughs in natural language processing for model pretraining on large quantities of data have opened the way for similar foundation models in computer vision.
SuperGlue: Learning Feature Matching with Graph Neural Networks
magicleap/SuperGluePretrainedNetwork
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CVPR 2020
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
mikacuy/pointnetvlad
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CVPR 2018
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.
Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
QVPR/Patch-NetVLAD
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CVPR 2021
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.
EigenPlaces: Training Viewpoint Robust Models for Visual Place Recognition
gmberton/auto_vpr
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ICCV 2023
Visual Place Recognition is a task that aims to predict the place of an image (called query) based solely on its visual features.
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.
GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization
VicenteVivan/geo-clip
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NeurIPS 2023
Worldwide Geo-localization aims to pinpoint the precise location of images taken anywhere on Earth.
