Image Super-resolution

Image Super-Resolution is an image enhancement and reconstruction technique that belongs to the class of methods aimed at recovering high-resolution images from low-resolution inputs, distinguished by its specific focus on restoring fine-scale details and textures through pixel-level refinement guided by prior knowledge or learned representations.

4.1K

Publications

371.1K

Citations

11.2K

Authors

2.2K

Institutions

Publications per year

2017–2026

2.7K

Authors

11.2K

  1. RT
    Radu Timofte

    ETH Zurich, Switzerland

    65 publications · 15.4K citations

    35

    h-index

  2. CD
    Chao Dong

    Shenzhen Institutes of Advanced Technology, China

    47 publications · 21.6K citations

    34

    h-index

  3. JJ
    Junjun Jiang

    Harbin Institute of Technology, China

    45 publications · 3.2K citations

    29

    h-index

  4. XG
    Xinbo Gao

    Xidian University, China

    46 publications · 4.4K citations

    28

    h-index

  5. LV
    Luc Van Gool

    ETH Zurich, Switzerland

    35 publications · 9.8K citations

    26

    h-index

1–5 of 11.2K

Venues

  1. IEEE Transactions on Image Processing

    197 publications · 31.9K citations

    88

    h-index

  2. IEEE Transactions on Geoscience and Remote Sensing

    131 publications · 10.1K citations

    60

    h-index

  3. arXiv (Cornell University)

    Repository · 210 publications · 14.2K citations

    49

    h-index

  4. 40

    h-index

  5. Remote Sensing

    86 publications · 5.5K citations

    38

    h-index

1–5