self-sca-ori
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Which model is really the best?
Hi,
There are several models available. Which model is the best? I am on the way of integrating your models into https://github.com/kornia/kornia and would like to make good general purpose defaults.
Also, one more question - am I right that your evaluation on the IMC did not use scale/ori for descriptor calculation, but only for AdaLAM filtering?
Hello, Dmytro.
To obtain the best model, you first run these scripts on your terminal:
cd trained_models bash download_sca_model.sh bash download_ori_model.sh
The best model for scale estimation is in the following directory:
trained_models/_0621_092607_resnet18_ori36_sca13_branchsca/best_model.pt
The best model for orientation estimation is in the following directory:
trained_models/_0213_121404_resnet18_ori36_sca13_branchori/best_model.pt
Yes, we don't use the scale and orientation for patch normalization (before the descriptor extraction stage) on the IMC dataset evaluation but only use the sca/ori in the AdaLAM filtering stage.
Thank you.
Thank you.
One more question - both models (scale and ori) also output other thing - ori and scale. So, what it is best single model? :)
Hello. Our proposed method is to train the scale and the orientation separately. We tried to train the joint model of scale/orientation, but the separately trained model performed better.
For that reason, the scale best model and the orientation best model are provided separately.
Thank you. And finally - have you checked if the performance degrades on the grayscale images?
No, I did not check the performance degrades on the grayscale images. Because we trained our model using RGB source image.