Image Retrieval On Roxford Medium
Metrics
mAP
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | mAP |
|---|---|
| google-landmarks-dataset-v2-a-large-scale | 74.2 |
| revisiting-oxford-and-paris-large-scale-image | 59.8 |
| aggregating-deep-convolutional-features-for | 39.8 |
| learning-and-aggregating-deep-local | 79.4 |
| cross-dimensional-weighting-for-aggregated | 42.4 |
| learning-super-features-for-image-retrieval-1 | 81.8 |
| large-scale-image-retrieval-with-attentive | 67.8 |
| emerging-properties-in-self-supervised-vision | 51.5 |
| large-scale-image-retrieval-with-attentive | 73.4 |
| end-to-end-learning-of-deep-visual | 60.9 |
| revisiting-oxford-and-paris-large-scale-image | 71.3 |
| instance-level-image-retrieval-using | 80.4 |
| revisiting-oxford-and-paris-large-scale-image | 60.4 |
| revisiting-oxford-and-paris-large-scale-image | 59.4 |
| learning-token-based-representation-for-image | 82.28 |
| 2408-03282 | 90.7 |
| dark-side-augmentation-generating-diverse-1 | 66.3 |
| revisiting-oxford-and-paris-large-scale-image | 60.6 |
| revisiting-oxford-and-paris-large-scale-image | 33.9 |
| fine-tuning-cnn-image-retrieval-with-no-human | 64.7 |
| hypergraph-propagation-and-community | 88.4 |
| revisiting-oxford-and-paris-large-scale-image | 66.3 |
| particular-object-retrieval-with-integral-max | 41.7 |