I have some questions about the loss function .ddpm’s label should be a prior information of gradually increasing noise. How did you modify it to calculate the loss between the enhanced image and the label image, which is reflected in the code?
This place has always confused me,Looking forward to your reply,thank you!
Hi, the loss function is based on the Maximum Likelihood Learning from $xt$ to $x{t-1}$. You can find this part in our paper Section 3.3 and the code in optimize_parameters.
Thank you for opening up your work!
I have some questions about the loss function .ddpm’s label should be a prior information of gradually increasing noise. How did you modify it to calculate the loss between the enhanced image and the label image, which is reflected in the code? This place has always confused me,Looking forward to your reply,thank you!