Concepedia

Animated Filtering

Animated Filtering is a method within the field of interactive filtering that employs animation techniques to dynamically visualize and facilitate the progressive refinement of data subsets based on user interactions.

3

Publications

176

Citations

6

Authors

5

Institutions

Publications per year

2017–2026

0

Parents

Publications

3

1–3 of 3

Authors

6

  1. MA
    Maneesh Agrawala

    University of California, Berkeley, United States

    2 publications · 161 citations

    2

    h-index

  2. JW
    Jue Wang

    Adobe Systems (United States), United States

    2 publications · 161 citations

    2

    h-index

  3. SM
    Steven M. Drucker

    Microsoft (United States), United States

    2 publications · 161 citations

    2

    h-index

  4. MF
    Michael F. Cohen

    Microsoft (United States), United States

    2 publications · 161 citations

    2

    h-index

  5. KW
    Kent Wittenburg

    Mitsubishi Electric (United States), United States

    1 publications · 15 citations

    1

    h-index

1–5 of 6

Institutions

5

  1. University of California, Berkeley

    Berkeley, United States

    2 h-index

    2 publications

    161 citations

  2. Microsoft Research (United Kingdom)

    Cambridge, United Kingdom

    2 h-index

    4 publications

    322 citations

  3. University of Washington

    Seattle, United States

    2 h-index

    2 publications

    161 citations

  4. Microsoft (United States)

    Redmond, United States

    1 h-index

    2 publications

    254 citations

  5. Core Competence

    Santa Fe, United States

    1 h-index

    2 publications

    30 citations

1–5 of 5

Venues

  1. ACM Transactions on Graphics

    TOG · 1 publications · 127 citations

    1

    h-index

1–1