Submission details
| Method name | NetVLAD (top-50) & D2-Net - multi-scale |
| Dataset | silda |
| Submission date | Sept. 26, 2019, 7:05 a.m. |
| Last modified | Nov. 1, 2019, 9:50 a.m. |
| Publication url | http://openaccess.thecvf.com/content_CVPR_2019/papers/Dusmanu_D2-Net_A_Trainable_CNN_for_Joint_Description_and_Detection_of_CVPR_2019_paper.pdf |
| Code url | https://github.com/mihaidusmanu/d2-net |
| Other info | Uses NetVLAD (bottom part cropped - 825x1000) to identify the top-50 closest database images, then uses multi-scale D2-Net features (bottom part cropped - 825x1000) for feature matching and COLMAP's image_registrator for localization. |
Detailed results for all conditions
| Method | evening | snow | night |
|---|---|---|---|
| NetVLAD (top-50) & D2-Net - multi-scale | 29.6 / 67.8 / 94.8 | 6.0 / 16.4 / 72.3 | 25.6 / 51.6 / 79.9 |