Trustworthy Image Super-Resolution via Generative Pseudoinverse
Abstract
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.
Cite
Text
Floros et al. "Trustworthy Image Super-Resolution via Generative Pseudoinverse." ICLR 2025 Workshops: DeLTa, 2025.Markdown
[Floros et al. "Trustworthy Image Super-Resolution via Generative Pseudoinverse." ICLR 2025 Workshops: DeLTa, 2025.](https://mlanthology.org/iclrw/2025/floros2025iclrw-trustworthy/)BibTeX
@inproceedings{floros2025iclrw-trustworthy,
title = {{Trustworthy Image Super-Resolution via Generative Pseudoinverse}},
author = {Floros, Andreas and Moosavi-Dezfooli, Seyed-Mohsen and Dragotti, Pier Luigi},
booktitle = {ICLR 2025 Workshops: DeLTa},
year = {2025},
url = {https://mlanthology.org/iclrw/2025/floros2025iclrw-trustworthy/}
}