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[CVPR2020] Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation

License: Other

Python 97.16% Shell 1.51% MATLAB 1.33%

multimodal registartion stn image-to-image-translation multi-modal multi-modal-learning affine-transformation deformable-transformation deep-learning cnn

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test code

where is test code ?

Please help me suggest the dataset and where dataloader?

Please help me suggest the dataset to follow the step 1.
where the dataloader if we have the dataset?
Thank you.

pretrained model

Hi，

Would you mind releasing your self-trained model,please?

test code

hi,is there no registration test code here?

Question re quality of generated images

Thanks for your paper and offering this code. I'm building on your code and modifying it for a different domain that has lower frequency textures than the plant images you used. I was wondering, how did the quality of your generated visible and/or thermal images turn out? I don't recall (and sorry if you reported it and I didn't see it), in your paper, if you reported FID scores or other metrics about the quality of the generated images. Thanks!

Can you provide the dataset you used?

Hello, could you provide the dataset you used or how can we get access to the commercial dataset? Appreciate it!

Why generated images are all full gray image(the value is zero)

I use the pretrained model "/checkpoints/experiment_name/latest_net_R.pth" to my dataset, but the image generated are all value of zero?

Test code

Where is test code?

can not find unet_stn.py

Hi,
I want to try a deformation field based registration network,but I did not find unet_stn.py,can you release it?

extremely grateful !

test.py is missing?

Really interesting work! I would love to try it out...
But it seems test.py is missing? (as pointed out also in #2)

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