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I have extracted features by using the pretrained model and matched them following this issue ,but the matching result seems not good enough, even when i matched the picture with its rotated one, there also are a lot of error pairs in result picture. Is there something i can do to promote the matching performance? May i need to retrain the model?
I am looking forward to your reply, thanks a lot!
here is the result when the picture were matched with its rotated one.
The text was updated successfully, but these errors were encountered:
Hi, which pretrained model are you using? In the TF-LIFT repo, there's a rotation invariant one. Maybe try that one? We also have lf-net which should also be better.
Hi Professor,thank you for sharing the code!
I have extracted features by using the pretrained model and matched them following this issue ,but the matching result seems not good enough, even when i matched the picture with its rotated one, there also are a lot of error pairs in result picture. Is there something i can do to promote the matching performance? May i need to retrain the model?
I am looking forward to your reply, thanks a lot!
here is the result when the picture were matched with its rotated one.
The text was updated successfully, but these errors were encountered: