Image-Based Localization
21 papers with code • 4 benchmarks • 6 datasets
Determining the location of an image without GPS based on cross-view matching. In most of the cases a database of satellite images is used to match the ground images to them.
Benchmarks
These leaderboards are used to track progress in Image-Based Localization
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Datasets
CVUSA
NAVER LABS Localization Datasets
Latest papers with no code
Fusing Convolutional Neural Network and Geometric Constraint for Image-based Indoor Localization
This paper proposes a new image-based localization framework that explicitly localizes the camera/robot by fusing Convolutional Neural Network (CNN) and sequential images' geometric constraints.
Digging Into Self-Supervised Learning of Feature Descriptors
Fully-supervised CNN-based approaches for learning local image descriptors have shown remarkable results in a wide range of geometric tasks.
Real-time Geo-localization Using Satellite Imagery and Topography for Unmanned Aerial Vehicles
The capabilities of autonomous flight with unmanned aerial vehicles (UAVs) have significantly increased in recent times.
Pose-GNN : Camera Pose Estimation System Using Graph Neural Networks
We propose a novel image based localization system using graph neural networks (GNN).
Joint Visual and Wireless Signal Feature based Approach for High-Precision Indoor Localization
The existing localization systems for indoor applications basically rely on wireless signal.
Combining Deep Learning with Geometric Features for Image based Localization in the Gastrointestinal Tract
Considering these, we propose a novel approach to combine DL method with traditional feature based approach to achieve better localization with small training data.
Large-scale, real-time visual-inertial localization revisited
Our approach spans from offline model building to real-time client-side pose fusion.
Learning Scene Geometry for Visual Localization in Challenging Conditions
We propose a new approach for outdoor large scale image based localization that can deal with challenging scenarios like cross-season, cross-weather, day/night and longterm localization.
Improving Image-Based Localization with Deep Learning: The Impact of the Loss Function
This work investigates the impact of the loss function on the performance of Neural Networks, in the context of a monocular, RGB-only, image localization task.
Privacy Preserving Image-Based Localization
Current localization systems rely on the persistent storage of 3D point clouds of the scene to enable camera pose estimation, but such data reveals potentially sensitive scene information.
