Trustworthy Image Super-Resolution via Generative Pseudoinverse

We consider the problem of trustworthy image restoration, taking the form of a constrained optimization over the prior density. To this end, we develop generative models for the task of image super-resolution that respect the degradation process and that can be made asymptotically consistent with the low-resolution measurements, outperforming existing methods by a large margin in that respect.

@article{floros2025_2505.12375,
  title={ Trustworthy Image Super-Resolution via Generative Pseudoinverse },
  author={ Andreas Floros and Seyed-Mohsen Moosavi-Dezfooli and Pier Luigi Dragotti },
  journal={arXiv preprint arXiv:2505.12375},
  year={ 2025 }
}