Methods › General › Inference Attack › Canvas Method
Canvas Method
Introduced by Yeachan Park et al. in Membership Inference Attacks Against Object Detection Models
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Canvas Method is a method for inference attacks on object detection models. It draws a predicted bounding box distribution on an empty canvas for an attack model input. The canvas is initially set to an image of 300×300 pixels in size, where every pixel has a value of zero and the boxes drawn on the canvas have the same center as the predicted boxes and the same intensity as the prediction scores.
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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Membership Inference Attacks Against Object Detection Models 12 Jan 2020 · 1 repository · arXiv:2001.04011
Tasks archive 2025-07-28
5 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 |
|---|---|
| Inference Attack | 1 |
| Membership Inference Attack | 1 |
| Object | 1 |
| Object Detection | 1 |
| object-detection | 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