Methods › Computer Vision › Image Feature Extractors › Involution

Involution

5 papers tagged archive 2025-07-28

Introduced by Duo Li et al. in Involution: Inverting the Inherence of Convolution for Visual Recognition

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

Involution is an atomic operation for deep neural networks that inverts the design principles of convolution. Involution kernels are distinct in the spatial extent but shared across channels. If involution kernels are parameterized as fixed-sized matrices like convolution kernels and updated using the back-propagation algorithm, the learned involution kernels are impeded from transferring between input images with variable resolutions.

The authors argue for two benefits of involution over convolution: (i) involution can summarize the context in a wider spatial arrangement, thus overcome the difficulty of modeling long-range interactions well; (ii) involution can adaptively allocate the weights over different positions, so as to prioritize the most informative visual elements in the spatial domain.

PaperSource

Papers archive 2025-07-28

5 shown of 5, 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

10 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
Classification1
Computational Efficiency1
Image Classification1
Image Generation1
Image Super-Resolution1
Object Detection1
SSIM1
Small Object Detection1
Super-Resolution1
object-detection1

Usage over time archive 2025-07-28

Papers per year tagged with Involution: 2021 to 2025, peak 2 2 0 2021: 2 papers 2021 2022: 1 paper 2022 2023: 0 papers 2023 2024: 1 paper 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (5 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

Image Feature Extractors

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