Patch-based Matching

Patch-Based Matching is a template matching approach that identifies occurrences of a target pattern by comparing localized image regions or data patches against a reference template through similarity measures, distinguishing itself by operating on discretely sampled subregions rather than global image structures.

122

Publications

13.9K

Citations

421

Authors

190

Institutions

Publications per year

2017–2026

54

Variants

Patch Matching

Authors

421

  1. TK
    Timothy K. Shih

    National Central University, Taiwan

    4 publications · 77 citations

    4

    h-index

  2. ES
    Eli Shechtman

    Adobe Systems (United States), United States

    3 publications · 3.3K citations

    3

    h-index

  3. XW
    Xiaogang Wang

    European Organization for Nuclear Research, Switzerland

    3 publications · 1.7K citations

    3

    h-index

  4. RZ
    Rui Zhao

    Group Sense (China), China

    3 publications · 1.7K citations

    3

    h-index

  5. CB
    Connelly Barnes

    Adobe Systems (United States), United States

    3 publications · 3.4K citations

    3

    h-index

1–5 of 421

Venues

  1. Pattern Recognition Letters

    4 publications · 113 citations

    4

    h-index

  2. IEEE Transactions on Image Processing

    4 publications · 334 citations

    4

    h-index

  3. 3

    h-index

  4. ACM Transactions on Graphics

    TOG · 3 publications · 5.3K citations

    3

    h-index

  5. 3

    h-index

1–5