Comments (2)
yxgeee
commented on July 17, 2024
We did not train on these retrieval datasets (e.g. Oxford, Paris). We just show the generalization ability of our model by directly testing it. The same protocol was used by NetVLAD and SARE.
The one you mentioned, as well as the other works that focused on image retrieval, trained and tested their models on the same retrieval datasets. Thus they are not comparable with our methods.
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XiSHEN0220
commented on July 17, 2024
Thanks for your reply. :)
I close the issue.
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Related Issues (20)
- About negative samples HOT 3
- how the training set is set up HOT 1
- Evalution protocol
- Performances on Oxford and Paris HOT 6
- models for torch.hub
- .mat files HOT 3
- missing keys in state_dict HOT 1
- pitts 250k top-1 88.2% HOT 1
- About Normalize in get_transformer_train and get_transformer_test HOT 1
- reproduction problem HOT 9
- reproduction problem
- Extract descriptor of single image using models trained on custom datasets
- How to visualize the feature map like Fig.5 in paper?
- Reproducing SARE results
- Test on RParis and ROxford dataset
- about modify d=25 meters HOT 2
- Reproduce results on Tokyo247 dataset HOT 2
- authors dont reply, found a better repo
- Is the pretrained model also MIT? HOT 2
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