Some questions related to the paper

[a2bc]

Hello,
Thanks for your paper https://openaccess.thecvf.com/content_CVPR_2019/papers/Chen_Camera_Lens_Super-Resolution_CVPR_2019_paper.pdf and sharing code.

I would like to ask you some questions

1. For the section 6.1 in your paper "Advanced digital zoom"
   Once the training done, we have 3 trained networks BicubicSR, GaussianSR, CameraSR.
   To get the figure 8, figure 9 and figure 6b, what is input LR image that you use to inference with 3 above trained networks ?
   a. Is it always the low resolution image obtained from the camera for all 3 networks ?
   b. Or downsampled bicubic image for BicubicSR network; downsampled gaussian image for GaussianSR and low resolution image obtained from the camera for the CameraSR ?

If it is (a) then the explication is a domain gap between the the low resolution image obtained from the camera and the one with simulated method (bicubic or Gaussian) (you already mention this observation in section 5.1 :-) )

If it is (b) : ouf, I don't understand the logic of your work. Please give more information in this case

2. If it is (a), hence for the section 6.2. Generalizability : if we observe this generalization, it means that there is no (or if exist, very small) difference in degradation pipeline between different devices. And the bicubic/gaussian degradation is a simple model but it is not realistic at all.

Thanks !