**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.

**RealNVP** is a generative model that utilises real-valued non-volume preserving (real NVP) transformations for density estimation. The model can perform efficient and exact inference, sampling and log-density estimation of data points.

RealNVP

Density estimation using Real NVP

Canvas Method

Membership Inference Attacks Against Object Detection Models

**Deflation** is a video-to-image operation to transform a video network into a network that can ingest a single image. In the two types of video networks considered in the original paper, this deflation corresponds to the following operations: for [3D convolutional based networks](https://paperswithcode.com/method/3d-convolution), summing the 3D spatio-temporal filters over the temporal dimension to obtain 2D filters; for TSM networks,, turning off the channel shifting which results in a standard [residual architecture](https://paperswithcode.com/method/resnet) (ResNet50) for images.

Source	Membership Inference Attacks Against Object Detection Models
Year	2000
Data Source	CC BY-SA - https://paperswithcode.com