Evaluating Parameterization Methods for Convolutional Neural Network (CNN)-Based Image Operators

Seung-Wook Kim, Sung-Jin Cho, Kwang-Hyun Uhm, Seo-Won Ji, Sang-Won Lee, Sung-Jea Ko

CVPRW 2019 pp. 1862-1870

doi:10.1109/CVPRW.2019.00237 /cvprw/2019/kim2019cvprw-evaluating/

Abstract

Recently, deep neural networks have been widely used to approximate or improve image operators. In general, an image operator has some hyper-parameters that change its operating configurations, e.g., the strength of smoothing, up-scale factors in super-resolution, or a type of image operator. To address varying parameter settings, an image operator taking such parameters as its input, namely a parameterized image operator, is an essential cue in image processing. Since many types of parameterization techniques exist, a comparative analysis is required in the context of image processing. In this paper, we therefore analytically explore the operation principles of these parameterization techniques and study their differences. In addition, performance comparisons between image operators parameterized by using these methods are assessed experimentally on common image processing tasks including image smoothing, denoising, deblocking, and super-resolution.

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Cite

Text

Kim et al. "Evaluating Parameterization Methods for Convolutional Neural Network (CNN)-Based Image Operators." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019. doi:10.1109/CVPRW.2019.00237

Markdown

[Kim et al. "Evaluating Parameterization Methods for Convolutional Neural Network (CNN)-Based Image Operators." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019.](https://mlanthology.org/cvprw/2019/kim2019cvprw-evaluating/) doi:10.1109/CVPRW.2019.00237

BibTeX

@inproceedings{kim2019cvprw-evaluating,
  title     = {{Evaluating Parameterization Methods for Convolutional Neural Network (CNN)-Based Image Operators}},
  author    = {Kim, Seung-Wook and Cho, Sung-Jin and Uhm, Kwang-Hyun and Ji, Seo-Won and Lee, Sang-Won and Ko, Sung-Jea},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2019},
  pages     = {1862-1870},
  doi       = {10.1109/CVPRW.2019.00237},
  url       = {https://mlanthology.org/cvprw/2019/kim2019cvprw-evaluating/}
}