Modulating Image Restoration With Continual Levels via Adaptive Feature Modification Layers

@article{He2019ModulatingIR,
  title={Modulating Image Restoration With Continual Levels via Adaptive Feature Modification Layers},
  author={Jingwen He and C. Dong and Y. Qiao},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019},
  pages={11048-11056}
}
  • Jingwen He, C. Dong, Y. Qiao
  • Published 2019
  • Computer Science
  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • In image restoration tasks, like denoising and superresolution, continual modulation of restoration levels is of great importance for real-world applications, but has failed most of existing deep learning based image restoration methods. Learning from discrete and fixed restoration levels, deep models cannot be easily generalized to data of continuous and unseen levels. This topic is rarely touched in literature, due to the difficulty of modulating well-trained models with certain hyper… CONTINUE READING
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