• Corpus ID: 237502987

Dynamic Attentive Graph Learning for Image Restoration

@article{Mou2021DynamicAG,
  title={Dynamic Attentive Graph Learning for Image Restoration},
  author={Chong Mou and Jian Zhang and Zhuoyuan Wu},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.06620}
}
Non-local self-similarity in natural images has been verified to be an effective prior for image restoration. However, most existing deep non-local methods assign a fixed number of neighbors for each query item, neglecting the dynamics of non-local correlations. Moreover, the non-local correlations are usually based on pixels, prone to be biased due to image degradation. To rectify these weaknesses, in this paper, we propose a dynamic attentive graph learning model (DAGL) to explore the dynamic… 

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