Methods › Computer Vision › Vision Transformers › Swin Transformer

Swin Transformer

416 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

The Swin Transformer is a type of Vision Transformer. It builds hierarchical feature maps by merging image patches (shown in gray) in deeper layers and has linear computation complexity to input image size due to computation of self-attention only within each local window (shown in red). It can thus serve as a general-purpose backbone for both image classification and dense recognition tasks. In contrast, previous vision Transformers produce feature maps of a single low resolution and have quadratic computation complexity to input image size due to computation of self-attention globally.

Source: Swin Transformer: Hierarchical Vision Transformer using...See Code · microsoft/Swin-Transformer

Papers archive 2025-07-28

30 shown of 416, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 353 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Semantic Segmentation91
Image Classification55
Object Detection50
Decoder47
Segmentation47
image-classification39
object-detection35
Image Segmentation29
Instance Segmentation25
Super-Resolution23
Transfer Learning23
Medical Image Segmentation22
Classification21
Data Augmentation20
Object19
Diagnostic15
Denoising13
Image Super-Resolution13
GPU12
Image Restoration12

Usage over time archive 2025-07-28

Papers per year tagged with Swin Transformer: 2021 to 2025, peak 109 109 0 2021: 45 papers 2021 2022: 107 papers 2022 2023: 109 papers 2023 2024: 106 papers 2024 2025: 49 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (416 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Vision Transformers

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