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View Code? Open in Web Editor NEWOfficial PyTorch Implementation of Correlation Verification for Image Retrieval, CVPR 2022 (Oral Presentation)
Official PyTorch Implementation of Correlation Verification for Image Retrieval, CVPR 2022 (Oral Presentation)
Hello, could you please provide CVNet training scripts and tutorials? Thank you
Hello sungonce, I can't download the training model, can you send to my email: [email protected]. Thank you very much!
It's an honor to see this excellent model. Can you please tell me how to train this model
Hi, could you please release the data list of gld after your cleaning?
First of all, thanks for your awesome work. The result is really impressive.
Here I felt confused about the training steps for GLDv2 clean version. In your paper, it is described as:
The global model is trained for 25 epochs (39.5M steps) for the training dataset, using a learning rate of 0.005625, and a batch size of 144.
And the GLDv2 clean set, as you wrote, has 1.58M images from 81k landmarks
.
Then obviously, if you want to train 25 epochs, then that means you train (1.58/144)*25 = 0.27M
steps, and for 39.5M steps, it is ~3657 epochs. So which description is correct, or did I just miss something?
Hi @sungonce, thanks for your impressive works and sharing!
I notice that you use the "torch.bmm( )" as the correlation process in "compute_crossscale_correlation( )" function. However in general, the correlation process between two images is represented as the equation bellow. Using the multiplication to represent the correlation between two images seems to be uncommon. So could you please explain the reason for such design? Sincerely for your reply!
dear sir,
How to train Google's data set and when it can be released?
Can you provide training codes
Hi,
Thanks for releasing the codes for this amazing work.
I just quickly took a look at the entire codes, and it seems that the codes for GLD-v2 is not there.
Is there any plan to release the pretrained weights and codes for GLD-v2 dataset?
Hello, thank you so much for the amazing work! It inspires me a lot.
May I ask if there is a (rough) date for the code to be released? I am looking forward to this masterpiece :)
Thank you very much for amazing work and papers.
I wanted to ask if you could add a license file to this code?
Alternatively, can you specify under what license it is published?
Regards
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