Image Retrieval On Rparis Hard
评估指标
mAP
评测结果
各个模型在此基准测试上的表现结果
比较表格
| 模型名称 | mAP |
|---|---|
| fine-tuning-cnn-image-retrieval-with-no-human | 56.3 |
| learning-super-features-for-image-retrieval-1 | 70.0 |
| learning-and-aggregating-deep-local | 62.4 |
| revisiting-oxford-and-paris-large-scale-image | 17.5 |
| learning-token-based-representation-for-image | 78.56 |
| instance-level-image-retrieval-using | 77.7 |
| revisiting-oxford-and-paris-large-scale-image | 44.7 |
| hypergraph-propagation-and-community | 83.3 |
| emerging-properties-in-self-supervised-vision | 51.6 |
| large-scale-image-retrieval-with-attentive | 55.4 |
| revisiting-oxford-and-paris-large-scale-image | 31.3 |
| aggregating-local-deep-features-for-image | 44.7 |
| revisiting-oxford-and-paris-large-scale-image | 31.2 |
| global-features-are-all-you-need-for-image | 86.7 |
| cross-dimensional-weighting-for-aggregated | 47.2 |
| particular-object-retrieval-with-integral-max | 59.4 |
| large-scale-image-retrieval-with-attentive | 69.3 |
| revisiting-oxford-and-paris-large-scale-image | 34.5 |
| revisiting-oxford-and-paris-large-scale-image | 35.0 |
| particular-object-retrieval-with-integral-max | 44.1 |
| google-landmarks-dataset-v2-a-large-scale | 70.3 |
| revisiting-oxford-and-paris-large-scale-image | 45.1 |
| 2408-03282 | 89.7 |