One Network to Solve Them All — Solving Linear Inverse Problems Using Deep Projection Models

@article{Chang2017OneNT,
  title={One Network to Solve Them All — Solving Linear Inverse Problems Using Deep Projection Models},
  author={Jen-Hao Rick Chang and Chun-Liang Li and Barnab{\'a}s P{\'o}czos and B. V. K. Vijaya Kumar and Aswin C. Sankaranarayanan},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={5889-5898}
}
While deep learning methods have achieved state-of-theart performance in many challenging inverse problems like image inpainting and super-resolution, they invariably involve problem-specific training of the networks. Under this approach, each inverse problem requires its own dedicated network. In scenarios where we need to solve a wide variety of problems, e.g., on a mobile camera, it is inefficient and expensive to use these problem-specific networks. On the other hand, traditional methods… CONTINUE READING
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