Reviews: Blind Super-Resolution Kernel Estimation using an Internal-GAN

The paper proposes a method for blind super-resolutions by estimating the kernel with a GAN. The method is based on zero-shot learning: it assumes unknown SR kernel, and thus estimates the kernel in a blind manner at test time. The method improves restoration quality by a large margin with the aid of the accurately estimated SR kernel. The paper is well written. Reviewers agreed since the beginning on the acceptance and are satisfied by the rebuttal.