Artifical Intelligence Chair - Deep Computational Imaging
Funded by ANR - French Agency for National Research

Deep Computational Imaging (DeepCim) is a three-year (2020-2023) project that, building upon the achievements of the ERC-CLIM, develops optimization and deep learning based solutions in computational imaging.

 
Jounal Publications
 

  • M. Le Pendu, C. Guillemot, Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Inverse Problems, submitted, IEEE Trans. on Pattern Analysis and Machine Intelligence, Aug. 2021.
  • G. Le Guludec, E. Miandji, C. Guillemot, Deep Light Field Acquisition Using Learned Coded Mask Distributions for Color Filter Array Sensors, IEEE Trans. on computational imaging, vol. 7, pp. 475-488, 2021, May 2021. [preprint]
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    Conference Publications
     

  • R. Fermanian, M. Le Pendu, C. Guillemot, Regularizing the Deep Image Prior with a Learned Denoiser for Linear Inverse Problems, IEEE MultiMedia Signal Processing workshop, accepted, 6-8 Oct. 2021. [More] [preprint]