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Thanks for your great work!
When reading the paper, I had the following questions:
1. Where can I find the deraining results without pretraining?
2. From the following table, it can be seen tha…
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Thanks for sharing this great work. Equivariant Imaging is a great idea. However, I have a few questions about the mechanism/motivation of this idea.
Yes, clean signals are hard to obtain in many c…
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hi,this is great work. I want to use this network for single image deraining, and what parts of this code can I modify? Or do you have any good suggestions? thanks!
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Hi there, 1st of all thanks for your work, your wrapper is very clean and usable.
If you're interested can you build something similar for [HINet: Half Instance Normalization Network for Image Rest…
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When I finished the training and tested it, the program reported an error.
===>Testing using weights: ./checkpoints/Deraining/models/MPRNet/model_best.pth
0%| …
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the dataset has1800 training data, 200 test data,
Why the loss is so high, I try to change the learning rate to 1.5e-4. but it is no helpful
![image](https://user-images.githubusercontent.com/1221…
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![image](https://user-images.githubusercontent.com/12219867/119628806-03733b80-be40-11eb-935b-c7d739538768.png)
I would like to compare the performance of these two real rain images, can you send me …
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Hi!
Thank you so much for your work!
I am wondering if anyone can run the model on PyTorch 1.8.1(stable version)?
Thanks
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Hi, Dr Liu
Thanks for your great job!
I check the testing codes provided by this work, different tasks use different PSNR computation.
E.g.
(1) Denosing: the average channels of PSNR
(2) Derainin…