an issue about the results of paper model.

[Lininggggggg]

hello, i have an issue is about the compared model of FSRCNN(origin), and your model of FSRCNN training by PISR.
the origin model of fsrcnn is trained without div2k, but your model has.
so, maybe your method is no good as your paper shows, because if the origin model of fsrcnn is trained with the same trainset like yours, it will better than before, right?

if i am wrong, could you tell me why, please?
thanks you very much!

[Lininggggggg]

emm，ok, i am sorry. i am wrong.
you had deal with this problem in the paper.
thanks you for your excellent work!

[Lininggggggg]

sorry, i still have another problem.
the multiadds of fsrcnn is false, and the reason maybe is the package you used to count flops is error.(the deconv stride is the same as upscale, so the correct flops should be 0.738259GMac.)
you can check it by the origin paper or use the package like "from thop import profile".

[Lininggggggg]

i hope you can reply me.
thank you very much!!!