Photo Geolocation Estimation On Im2Gps
Métriques
City level (25 km)
Continent level (2500 km)
Country level (750 km)
Median Error (km)
Reference images
Region level (200 km)
Street level (1 km)
Training images
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | City level (25 km) | Continent level (2500 km) | Country level (750 km) | Median Error (km) | Reference images | Region level (200 km) | Street level (1 km) | Training images |
|---|---|---|---|---|---|---|---|---|
| pigeon-predicting-image-geolocations | 40.9 | 91.1 | 82.3 | 70.5 | 4.5M | 63.3 | 14.8 | 4.5M |
| geolocation-estimation-of-photos-using-a | 35.0 | 79.7 | 64.1 | - | 0 | 49.8 | 13.5 | 4.7M |
| planet-photo-geolocation-with-convolutional | 18.1 | 65.8 | 45.6 | - | 0 | 30.0 | 6.3 | 6.2M |
| revisiting-im2gps-in-the-deep-learning-era | 33.3 | 71.3 | 57.4 | - | 0 | 44.3 | 12.2 | 6M |
| revisiting-im2gps-in-the-deep-learning-era | 33.3 | 73.4 | 61.6 | - | 28M | 47.7 | 14.4 | 6M |
| geolocation-estimation-of-photos-using-a | 43.0 | 80.2 | 66.7 | - | 0 | 51.9 | 16.9 | 4.7M |
| planet-photo-geolocation-with-convolutional | 24.5 | 71.3 | 53.6 | - | 0 | 37.6 | 8.4 | 91M |
| cplanet-enhancing-image-geolocalization-by | 37.1 | 78.5 | 62.0 | - | 0 | 46.6 | 16.5 | 30.3M |
| revisiting-im2gps-in-the-deep-learning-era | 21.9 | 63.7 | 49.4 | - | 0 | 34.6 | 6.8 | 6M |
| geolocation-estimation-of-photos-using-a | 40.9 | 78.5 | 65.4 | - | 0 | 51.5 | 15.2 | 4.7M |
| learning-generalized-zero-shot-learners-for | 28.3 | 88.2 | 74.7 | - | 0 | 45.1 | - | 1.1M |