Hello. I have been researching deep learning super-resolution networks.
The problem is that I never get the same results shown on published papers when I create the exact same network with the exact same settings using PyTorch.
I get 0.3dB~0.5dB lower performance which is a big deal in super-resolution.
Is there something these guys do to the model to improve results?
Do they use a lower-level language?
How do they tweak their performance using the presented datasets?