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Reproducing the Video Denoiser

Open gauenk opened this issue 2 years ago • 7 comments

Hello RVRT Team :wave: Thank you again for your great code.

I have followed your paper's instructions to train my own RVRT model. However, my network's quality does not match the network you share online, nor the numbers you report.

Maybe I have missed something on my end, but I want to know if you have a training script so I can inspect all the details myself?

Thank you.

gauenk avatar Aug 18 '23 14:08 gauenk

I am gently following up on the previous comment.

gauenk avatar Aug 29 '23 14:08 gauenk

I caught the same problem with you, even though the iterator number more than 20000 times, the loss almost stay the same(8e-2). Thus the infference results of the new-trained model is still far from the pre-trained one.

Dawson0813 avatar Aug 31 '23 10:08 Dawson0813

As a researcher with limited GPUs, your comment means more to me than you know.

gauenk avatar Sep 06 '23 17:09 gauenk

As a researcher with limited GPUs, your comment means more to me than you know.

Thank you for your kindly reply too. I wonder whether you have solved above issues. Last week I used a small trainning-sets to verify the RVRT network, but both the training loss and the test PSNR still stay the same.

Dawson0813 avatar Sep 07 '23 02:09 Dawson0813

The test results of author's pre-trained model is realy good, thanks again for their great work. I am sure that I have missed some key procedures in my training too, and I am also eagerly looking forward to get some more details from the RVRT team.

Dawson0813 avatar Sep 07 '23 02:09 Dawson0813

My issue is still unresolved.

gauenk avatar Sep 09 '23 19:09 gauenk

The test results of author's pre-trained model is realy good, thanks again for their great work. I am sure that I have missed some key procedures in my training too, and I am also eagerly looking forward to get some more details from the RVRT team.

Have you solved the problem? I am also facing the same issue where the training loss remains at nearly 8e-2 and does not converge.

zjuzhk avatar Dec 11 '24 03:12 zjuzhk