Visual Trend Mining

Visual Trend Mining is a systematic method within fashion trend forecasting that identifies and analyzes emerging aesthetic patterns from visual data sources to predict future design directions.

34

Publications

2K

Citations

107

Authors

45

Institutions

Publications per year

2017–2026

19

Authors

107

  1. KN
    Kawa Nazemi

    Darmstadt University of Applied Sciences, Germany

    4 publications · 71 citations

    4

    h-index

  2. DB
    Dirk Burkhardt

    Fraunhofer Institute for Computer Graphics Research, Germany

    4 publications · 71 citations

    4

    h-index

  3. KG
    Kristen Grauman

    The University of Texas at Austin, United States

    2 publications · 192 citations

    2

    h-index

  4. JM
    Julian McAuley

    University of California San Diego, United States

    2 publications · 213 citations

    2

    h-index

  5. RH
    Ruining He

    University of California San Diego, United States

    2 publications · 213 citations

    2

    h-index

1–5 of 107

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 268 citations

    3

    h-index

  2. Clothing and Textiles Research Journal

    2 publications · 39 citations

    2

    h-index

  3. IEEE Computer Graphics and Applications

    1 publications · 211 citations

    1

    h-index

  4. IEEE Signal Processing Magazine

    1 publications · 31 citations

    1

    h-index

  5. 2020 24th International Conference Information Visualisation (IV)

    Conference · 1 publications · 10 citations

    1

    h-index

1–5