Unrolled Optimization with Deep Priors

@article{Diamond2017UnrolledOW,
  title={Unrolled Optimization with Deep Priors},
  author={Steven Diamond and Vincent Sitzmann and Felix Heide and Gordon Wetzstein},
  journal={CoRR},
  year={2017},
  volume={abs/1705.08041}
}
A broad class of problems at the core of computational imaging, sensing, and low-level computer vision reduces to the inverse problem of extracting latent images that follow a prior distribution, from measurements taken under a known physical image formation model. Traditionally, hand-crafted priors along with iterative optimization methods have been used to solve such problems. In this paper we present unrolled optimization with deep priors, a principled framework for infusing knowledge of the… CONTINUE READING
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