Efficient and Concise Explanations for Object Detection with Gaussian-Class Activation Mapping Explainer

arXiv:2404.13417v1 Announce Type: new
Abstract: To address the challenges of providing quick and plausible explanations in Explainable AI (XAI) for object detection models, we introduce the Gaussian Class Activation Mapping Explainer (G-CAME). Our method efficiently generates concise saliency maps by utilizing activation maps from selected layers and applying a Gaussian kernel to emphasize critical image regions for the predicted object. Compared with other Region-based approaches, G-CAME significantly reduces explanation time to 0.5 seconds without compromising the quality. Our evaluation of …

abstract arxiv challenges class cs.ai cs.cv detection explainable ai explainer mapping maps object type xai