Review for NeurIPS paper: Cross-Scale Internal Graph Neural Network for Image Super-Resolution

Weaknesses: As in many SISR papers these days, the metric increase in PSNR and SSIM is vanishingly small. The qualitative example shown in Fig 3 demonstrates a more significant boost in metrics, however, this is obviously not reflected in the datasets as a whole given the average values reported in Table 1. I think it would be valid to state that this method mostly only helps in regions of self-similarity; it would be interesting to see if there is a metric that could capture this though rather than relying on anecdotal crops. The difference from previous graph convolutions applied for image restoration (like in [34]) seems fairly minor. Even the module as a whole is effectively a pretty small change to EDSR, involving very few additional layers.