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Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems (bibtex)
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems (bibtex)
by T. Meinhardt, M. Moeller, C. Hazirbas and D. Cremers
Reference:
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems (T. Meinhardt, M. Moeller, C. Hazirbas and D. Cremers), In IEEE International Conference on Computer Vision (ICCV), 2017. ([arxiv], [code])
Bibtex Entry:
@string{iccv="IEEE International Conference on Computer Vision (ICCV)"}
@inproceedings{meinhardt17learning,
 author = {T. Meinhardt and M. Moeller and C. Hazirbas and D. Cremers},
 title = {Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems},
 month = {October},
 year = {2017},
 booktitle = {IEEE International Conference on Computer Vision (ICCV)},
 keywords = {deep learning},
}
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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:
CVG Group DVL Group SRL Group