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    Computer vision & multimodal· 2021

    Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

    Ze Liu (first author) · 2021

    Read the original

    DOI 10.1109/iccv48922.2021.00986arXiv 2103.14030OpenAlex W3138516171

    On the reading lists

    Why it matters

    Introduced hierarchical shifted-window attention, making vision transformers practical for dense prediction tasks.

    Condensed from the expert lists' notes.

    The record

    First released
    2021 (from arXiv 2103.14030)
    Citations
    36,498 citations, as counted by Papers With Code (CC BY-SA 4.0)
    Named by
    both expert lists
    Score
    0.424 · computed rank 330 · consensus 0.11, must-read 0.5, citations percentile 0.975 (2020s · vision), awards 0, existing lists 0. Method

    Data sources

    Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.