Cross Modal Retrieval With Noisy 2
Metrics
Image-to-text R@1
Image-to-text R@10
Image-to-text R@5
R-Sum
Text-to-image R@1
Text-to-image R@10
Text-to-image R@5
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Image-to-text R@1 | Image-to-text R@10 | Image-to-text R@5 | R-Sum | Text-to-image R@1 | Text-to-image R@10 | Text-to-image R@5 |
|---|---|---|---|---|---|---|---|
| learning-from-noisy-correspondence-with-tri | 76.2 | 98.3 | 95.8 | 508.7 | 60.5 | 92.7 | 85.2 |
| cross-modal-retrieval-with-noisy | 77.4 | 97.3 | 95.0 | 502.3 | 58.7 | 89.8 | 84.1 |
| ugncl-uncertainty-guided-noisy-correspondence | 78.4 | 97.8 | 95.8 | 505.6 | 59.8 | 89.5 | 84.3 |
| cross-modal-active-complementary-learning-1 | 77.9 | 98.3 | 95.4 | 507.8 | 60.9 | 90.6 | 84.7 |
| noisy-correspondence-learning-with-self | 79.5 | 97.9 | 94.2 | 507.8 | 61.2 | 90.2 | 84.8 |
| mitigating-noisy-correspondence-by | 78.3 | 97.8 | 94.6 | 505.8 | 60.1 | 90.5 | 84.5 |
| noisy-correspondence-learning-with-meta | 77.4 | 97.6 | 94.9 | 501.9 | 59.6 | 89.2 | 83.2 |
| nac-mitigating-noisy-correspondence-in-cross | 79.3 | 97.8 | 94.6 | 507.1 | 60.8 | 90.1 | 84.5 |
| learning-to-rematch-mismatched-pairs-for | 77.9 | 97.8 | 95.2 | 503.8 | 59.8 | 89.5 | 83.6 |
| learning-with-noisy-correspondence | 76.3 | 96.9 | 93.7 | 498.9 | 58.4 | 89.8 | 83.8 |
| bicro-noisy-correspondence-rectification-for | 78.1 | 97.5 | 94.4 | 504.7 | 60.4 | 89.9 | 84.4 |
| repair-rank-correlation-and-noisy-pair-half | 79.2 | 96.9 | 95.0 | 504.4 | 59.4 | 89.5 | 84.4 |
| recon-enhancing-true-correspondence-1 | 80.3 | 97.8 | 95.3 | 511.8 | 61.6 | 91.3 | 85.5 |
| learning-with-noisy-correspondence-for-cross | 75.0 | 97.5 | 93.9 | 496.7 | 58.3 | 89.0 | 83.0 |
| deep-evidential-learning-with-noisy | 77.5 | 97.0 | 93.8 | 494.7 | 56.1 | 88.5 | 81.8 |
| cross-modal-retrieval-with-partially | 74.2 | 96.9 | 91.8 | 487.2 | 55.6 | 87.5 | 81.2 |