gmberton/deep-visual-geo-localization-benchmark
Official code for CVPR 2022 (Oral) paper "Deep Visual Geo-localization Benchmark"
This tool helps researchers and engineers evaluate and compare different visual geo-localization (VG) techniques. You input a collection of geographically tagged images (like from a self-driving car dataset) and it outputs performance metrics (like recall) for various VG methods. It's designed for anyone working on improving the accuracy of location recognition using visual data.
251 stars. No commits in the last 6 months.
Use this if you need to rigorously test and benchmark different computer vision models for their ability to accurately determine a location from images.
Not ideal if you're looking for a ready-to-use application for everyday image-based navigation or real-time location services without extensive setup.
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251
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31
Language
Python
License
MIT
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Last pushed
Jan 29, 2025
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