Patch Tracking

Patch Tracking is a methodological framework within the domain of computer vision that integrates spatiotemporal coherence and feature correspondence to maintain the identity of image patches across sequential frames or hierarchical feature maps in a manner consistent with their geometric and semantic evolution.

27

Publications

1.3K

Citations

89

Authors

53

Institutions

Publications per year

2017–2026

11

Authors

89

  1. RS
    Richard Szeliski

    Microsoft (United States), United States

    2 publications · 27 citations

    2

    h-index

  2. NC
    Nick C. Tang

    Institute of Information Science, Academia Sinica, Taiwan

    2 publications · 108 citations

    2

    h-index

  3. SB
    Sing Bing Kang

    Microsoft (United States), United States

    2 publications · 27 citations

    2

    h-index

  4. HS
    Heung‐Yeung Shum

    Microsoft Research Asia (China), China

    2 publications · 27 citations

    2

    h-index

  5. TK
    Timothy K. Shih

    National Central University, Taiwan

    2 publications · 108 citations

    2

    h-index

1–5 of 89

Venues

  1. 3

    h-index

  2. Neurocomputing

    2 publications · 74 citations

    2

    h-index

  3. IEEE Transactions on Image Processing

    1 publications · 25 citations

    1

    h-index

  4. Medical Image Analysis

    1 publications · 22 citations

    1

    h-index

  5. IEEE INFOCOM 2022 - IEEE Conference on Computer Communications

    Conference · 1 publications · 38 citations

    1

    h-index

1–5