Methods › Computer Vision › Image Data Augmentation › R-Mix
Random Mix-up
R-Mix
Introduced by Minh-Long Luu et al. in Expeditious Saliency-guided Mix-up through Random Gradient Thresholding
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
R-Mix (Random Mix-up) is a Mix-up family Data Augmentation method. It combines random Mix-up with Saliency-guided mix-up, producing a procedure that is fast and performant, while reserving good characteristics of Saliency-guided Mix-up such as low Expected Calibration Error and high Weakly-supervised Object Localization accuracy.
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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Expeditious Saliency-guided Mix-up through Random Gradient Thresholding 9 Dec 2022 · 1 repository · arXiv:2212.04875
Tasks archive 2025-07-28
4 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 |
|---|---|
| Classifier calibration | 1 |
| Image Classification | 1 |
| Object Localization | 1 |
| Weakly-Supervised Object Localization | 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