Photo Geolocation Estimation On Im2Gps
평가 지표
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
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | 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 |