Photo Geolocation Estimation On Yfcc26K
Metriken
City level (25 km)
Continent level (2500 km)
Country level (750 km)
Region level (200 km)
Street level (1 km)
Training Images
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | City level (25 km) | Continent level (2500 km) | Country level (750 km) | Region level (200 km) | Street level (1 km) | Training Images | Paper Title | Repository |
|---|---|---|---|---|---|---|---|---|
| Translocator | 17.8 | 60.6 | 41.3 | 28.0 | 7.2 | 4.7M | Where in the World is this Image? Transformer-based Geo-localization in the Wild | |
| ISNs (M, f*, S3) | 12.3 | 50.7 | 31.9 | 19.0 | 5.3 | 4.7M | Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification | - |
| GeoDecoder | 23.9 | 69.0 | 49.6 | 34.1 | 10.1 | 4.7M | Where We Are and What We're Looking At: Query Based Worldwide Image Geo-localization Using Hierarchies and Scenes | - |
| GeoCLIP | 22.2 | 76.0 | 57.5 | 36.7 | 11.6 | 4.7M | GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization | |
| PIGEOTTO | 25.8 | 79.0 | 63.2 | 42.7 | 10.5 | 4.5M | PIGEON: Predicting Image Geolocations | |
| PlaNet | 11.0 | 47.7 | 28.5 | 16.9 | 4.4 | 30.3M | PlaNet - Photo Geolocation with Convolutional Neural Networks |
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