StyleGAN.pytorch VS Ghost-DeblurGAN

I've still yet to try this one: https://github.com/huangzh13/StyleGAN.pytorch but at this point it might just be worth trying the Jupiter thingie. I sort of understand what it is.

You could try some sort of Image restoration GAN to produce a modified output of the input image (which lies on the curved surface). I have conducted research on GANs for deblurring Fiducial markers, and simply put, the Network takes a blurred image containing fiducial markers and outputs a ‘deblurred image’ whose fiducial markers can be more easily detected. However, keep in mind that the GANs can perform a wide variety of operations on an input Image (other than just deblurring), hence, they are called Image restoration networks in general. What you could give a shot is, create a pipeline where the captured image goes into the GAN, then the output is fed to the Apriltag detector. Here is the link to our GitHub if you need a starter: https://github.com/York-SDCNLab/Ghost-DeblurGAN, and some of my other suggestions are NAFNet and HINet.