Photo Geolocation Estimation On Im2Gps
评估指标
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
评测结果
各个模型在此基准测试上的表现结果
比较表格
| 模型名称 | 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 |