Canvas Method

Introduced by Park et al. in Membership Inference Attacks Against Object Detection Models

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$\times$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.

Source: Membership Inference Attacks Against Object Detection Models

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Papers

Paper	Code	Results	Date	Stars

Tasks

Task	Papers	Share
Inference Attack	1	33.33%
Membership Inference Attack	1	33.33%
Object Detection	1	33.33%

Usage Over Time

This feature is experimental; we are continuously improving our matching algorithm.

Components

Component	Type	Add Remove
🤖 No Components Found	You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories

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Inference Attack