LFI-CAM: Learning Feature Importance for Better Visual Explanation

Understand

Class Activation Mapping (CAM) is a powerful technique used to understand the decision making of Convolutional Neural Network (CNN) in computer vision.

• Recently, there have been attempts not only to generate better visual explanations, but also to improve classification performance using visual explanations.
• However, the previous works still have their own drawbacks.
• In this paper, we propose a novel architecture, LFI-CAM, which is trainable for image classification and visual explanation in an end-to-end manner.