Closed APichou closed 1 month ago
Hi!
The training scenes are mostly moderately complex scenes (e.g. architectural), not simple synthetic ones. The training images don't focus on particular features but are more general, with random camera views.
The following paper contains some useful details on how to create a good dataset for denoising: https://balint.io/nppd/ This isn't what OIDN is using but the approach described in this paper should work really well.
Hi! Thank you very much for sharing this info, this is very interesting and helpful!
Hello there!
I am curious about the kind of data sets the denoiser was initially trained on to get the result you can have right now by default. I have a series of questions for you if you don't mind:
Please tell me more on how you managed to make it work so well, I am really curious!
Thanks in advance!