Note: the models and results here are trained by this repo. In order to accomodate computation efficiency, we use small channel dimensions (64*3) and feature sizes of 128/2 X 128/2. We encourage you to change the channel dimensions and feature sizes to increase the performance.
| Model | Trained on | Tested on | Recall@1 | Recall@5 | Recall@10 | Download Link |
|---|---|---|---|---|---|---|
| small-model (for one V100 GPU) | Pitts30k-train | Pitts30k-test | 61.5% | 76.9% | 82.6% | Google Drive |
| middle-model (for both efficiency and performance) | Pitts30k-train | Pitts30k-test | 65.5% | 80.6% | 85.5% | Google Drive |
| large-model (the proposed one in paper) | Pitts30k-train | Pitts30k-test |