Retinal Image Matching on FIRE (full)
0Failed RateSIFT
Evaluation Results
| Method | Links | |||||||
|---|---|---|---|---|---|---|---|---|
| SIFT2023.07 | 0 | 20.15 | 79.85 | 0.903 | 0.474 | 0.341 | 0.573 | |
| REMPE2023.07 | 0 | 2.99 | 97.01 | 0.958 | 0.66 | 0.542 | 0.72 | |
| SuperPoint2023.07 | 0 | 5.22 | 94.78 | 0.882 | 0.649 | 0.49 | 0.674 | |
| GLAMpoints2023.07 | 0 | 7.46 | 92.54 | 0.85 | 0.543 | 0.474 | 0.622 | |
| R2D22023.07 | 0 | 12.69 | 87.31 | 0.9 | 0.517 | 0.386 | 0.601 | |
| NCNet2023.07 | 0 | 37.31 | 62.69 | 0.588 | 0.386 | 0.077 | 0.35 | |
| SuperRetina2023.07 | 0 | 1.5 | 98.5 | 0.94 | 0.783 | 0.542 | 0.755 | |
| Ours-1 (Large kernel-SuperRetina)Large kernel=true2023.07 | 0 | 0.75 | 99.25 | 0.942 | 0.783 | 0.558 | 0.761 | |
| Ours-2 (Swin UNETR-SuperRetina)Backbone=Swin UNETR, Reverse Knowledge Distillation=true, Dropout=50%2023.07 | 0 | 0 | 100 | 0.935 | 0.78 | 0.55 | 0.755 | |
| PBO2023.07 | 0.75 | 28.36 | 70.89 | 0.844 | 0.691 | 0.122 | 0.552 | |
| SuperGlue2023.07 | 0.75 | 3.73 | 95.52 | 0.885 | 0.689 | 0.488 | 0.687 |