Explaining decision of model from its prediction

Code

• github.com/Dipeshtamboli/Interactive-GradCAM
  OfficialIn paperpytorch★ 2

Abstract

This document summarizes different visual explanations methods such as CAM, Grad-CAM, Localization using Multiple Instance Learning - Saliency-based methods, Saliency-driven Class-Impressions, Muting pixels in input image - Adversarial methods and Activation visualization, Convolution filter visualization - Feature-based methods. We have also shown the results produced by different methods and a comparison between CAM, GradCAM, and Guided Backpropagation.

Tasks

Reproductions