Cross-view Comparison

Cross-View Comparison is a methodological framework within the domain of Coordinated Multiple Views that enables the systematic analysis and juxtaposition of data or representations across distinct visual or conceptual perspectives to identify correspondences, discrepancies, and patterns that are not evident within a single view.

28

Publications

1.5K

Citations

98

Authors

44

Institutions

Publications per year

2017–2026

21

Authors

98

  1. SZ
    Song‐Chun Zhu

    University of California, Los Angeles, United States

    3 publications · 414 citations

    3

    h-index

  2. WZ
    Wei‐Shi Zheng

    Sun Yat-sen University, China

    3 publications · 317 citations

    3

    h-index

  3. ZL
    Ziwei Liu

    Nanyang Technological University, Singapore

    2 publications · 77 citations

    2

    h-index

  4. XW
    Xudong Wang

    Shanghai Jiao Tong University, China

    2 publications · 77 citations

    2

    h-index

  5. XL
    Xiaobai Liu

    San Diego State University, United States

    2 publications · 396 citations

    2

    h-index

1–5 of 98

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 86 citations

    4

    h-index

  2. 3

    h-index

  3. IEEE Transactions on Cybernetics

    2 publications · 59 citations

    2

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 401 citations

    2

    h-index

  5. 1

    h-index

1–5