Methods › Computer Vision › Image Model Blocks › Residual SRM
Residual SRM
Introduced by HyunJae Lee et al. in SRM : A Style-based Recalibration Module for Convolutional Neural Networks
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A Residual SRM is a module for convolutional neural networks that uses a Style-based Recalibration Module within a residual block like structure. The Style-based Recalibration Module (SRM) adaptively recalibrates intermediate feature maps by exploiting their styles.
Papers archive 2025-07-28
1 shown of 1, 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.
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SRM : A Style-based Recalibration Module for Convolutional Neural Networks 26 Mar 2019 · 1 repository · arXiv:1903.10829Syntology ran 3 of 3 samples · 0 unverified · 2 pointer-only (licence)
Tasks archive 2025-07-28
2 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Image Classification | 1 |
| Style Transfer | 1 |
Usage over time archive 2025-07-28
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
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections