Comments (1)
Hello. I have no idea about the gap neither. I remember there is a hyperparameter (learning rate) I used is different from the original paper, but I forgot whether it was for the denoising task. Although hyperparameters matter sometimes but I don't think that's the main reason, I modified it just because I couldn't reproduce the performance with the same hyperparams. And I think that might be a written mistake.
No matter whether the learning rate does matter, you can check it in ./train.py and try to retrain it with the same hyperparams as the paper said, if necessary.
If you have other questions, feel free to contact me or open a new issue.
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Related Issues (19)
- information about trained models HOT 1
- TypeError: __init__() missing 1 required positional argument: 'task' HOT 3
- SR results not clear HOT 2
- Why SR results is one output image? HOT 4
- 2x model HOT 4
- Issue in SSIM implementation HOT 2
- evaluate.py can only output 1 frame from 7 LR frames? HOT 1
- some error
- Question About Super Resolution HOT 1
- the mask network
- run.py has some detail to modify
- ValueError: Floating point image RGB values must be in the 0..1 range.
- "tiny.zip" download link failed! HOT 2
- About the evaluation results HOT 3
- problems when using pytoflow HOT 7
- run.py forward() takes 2 positional arguments but 3 were given HOT 4
- VHS Denoise Model + Training Set HOT 2
- License?
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