The SR_loss has a error

[Hanv2]

the gt should not be downsampled

[JasonGUTU]

Thanks for your interest.
According to Eq.(7) of the paper, The $I_{LR}$ is actually obtained by downsampling the ground truth.
In other words, If we know the ground truth, we don't need to super-resolve the LR image anymore : )

[QingLicsaggie]

JasonGUTU: You answer is confusing. Then how to reproduce your paper results with the codes?

[a878322125]

In super resolution ，Should I input a 64 low definition image, sr factor can't change if i want to input 32*32 image

[JasonGUTU]

Hi, @QingLicsaggie and @a878322125 .
According to Eq.(7) of the paper, The optimization objective is set to be the likelihood of the SR problem that the super-resolved high-res image should have the same downsampled version with the ground-truth image's downsampled version, or the provided low-res image (which are regarded as a downsampled version of the ground truth high-res image). That is why the loss is calculated at the downsampled inversion images and ground truth.

[a878322125]

@JasonGUTU
Thank you for your explanation，target_images of code should input a 64*64 lr_image but the sr_image looks terrible.how to eproduce your paper results with the codes?

[JasonGUTU]

@JasonGUTU
Thank you for your explanation，target_images of code should input a 64*64 lr_image but the sr_image looks terrible.how to eproduce your paper results with the codes?

Did you test the code using the aligned face images? If you input a 64*64 lr_image, then you don't need to downsample it when calculating the loss. You can send me emails for more details: [email protected]