| PIGEOTTO | 40.9 | 91.1 | 82.3 | 70.5 | 4.5M | 63.3 | 14.8 | 4.5M | PIGEON: Predicting Image Geolocations | |
| CPlaNet (1-5, PlaNet) | 37.1 | 78.5 | 62.0 | - | 0 | 46.6 | 16.5 | 30.3M | CPlaNet: Enhancing Image Geolocalization by Combinatorial Partitioning of Maps | - |
| Im2GPS ([L] KNN, sigma=4) | 33.3 | 71.3 | 57.4 | - | 0 | 44.3 | 12.2 | 6M | Revisiting IM2GPS in the Deep Learning Era | - |
| Im2GPS (... 28m database) | 33.3 | 73.4 | 61.6 | - | 28M | 47.7 | 14.4 | 6M | Revisiting IM2GPS in the Deep Learning Era | - |
| StreetCLIP (Zero-Shot) | 28.3 | 88.2 | 74.7 | - | 0 | 45.1 | - | 1.1M | Learning Generalized Zero-Shot Learners for Open-Domain Image Geolocalization | |
| PlaNet (91M) | 24.5 | 71.3 | 53.6 | - | 0 | 37.6 | 8.4 | 91M | PlaNet - Photo Geolocation with Convolutional Neural Networks | |
| Im2GPS ([L] 7011C) | 21.9 | 63.7 | 49.4 | - | 0 | 34.6 | 6.8 | 6M | Revisiting IM2GPS in the Deep Learning Era | - |
| PlaNet (6.2M) | 18.1 | 65.8 | 45.6 | - | 0 | 30.0 | 6.3 | 6.2M | PlaNet - Photo Geolocation with Convolutional Neural Networks | |