Outdoor Localization
8 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Outdoor Localization
Most implemented papers
Panoramic Annular Localizer: Tackling the Variation Challenges of Outdoor Localization Using Panoramic Annular Images and Active Deep Descriptors
The panoramic annular images captured by the single camera are processed and fed into the NetVLAD network to form the active deep descriptor, and sequential matching is utilized to generate the localization result.
ROVER: A Multi-Season Dataset for Visual SLAM
To address this gap, we present ROVER, a comprehensive benchmark dataset tailored for evaluating visual SLAM algorithms under diverse environmental conditions and spatial configurations.
Real-time Outdoor Localization Using Radio Maps: A Deep Learning Approach
Global Navigation Satellite Systems typically perform poorly in urban environments, where the likelihood of line-of-sight conditions between devices and satellites is low.
CrossLocate: Cross-modal Large-scale Visual Geo-Localization in Natural Environments using Rendered Modalities
By combining the rendered database views with existing datasets of photographs (used as ''queries'' to be localized), we create a unique benchmark for visual geo-localization in natural environments, which contains correspondences between query photographs and rendered database imagery.
SGLoc: Scene Geometry Encoding for Outdoor LiDAR Localization
In this work, we propose a novel LiDAR localization framework, SGLoc, which decouples the pose estimation to point cloud correspondence regression and pose estimation via this correspondence.
BEV-CV: Birds-Eye-View Transform for Cross-View Geo-Localisation
Cross-view image matching for geo-localisation is a challenging problem due to the significant visual difference between aerial and ground-level viewpoints.
Representing 3D sparse map points and lines for camera relocalization
Recent advancements in visual localization and mapping have demonstrated considerable success in integrating point and line features.
SpaGBOL: Spatial-Graph-Based Orientated Localisation
SpaGBOL achieves state-of-the-art accuracies on the unseen test graph - with relative Top-1 retrieval improvements on previous techniques of 11%, and 50% when filtering with Bearing Vector Matching on the SpaGBOL dataset.