Manhattan and Correlation distance metrics best align CAM saliency maps with human perception on ImageNet chihuahuas, ranking LayerCAM, Score-CAM, and IS-CAM highest when compared to crowdsourced choices via RBO.
Available: https://arxiv.org/abs/2010.03023
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How Can One Choose the Best CAM-Based Explainability Method for a CNN Model?
Manhattan and Correlation distance metrics best align CAM saliency maps with human perception on ImageNet chihuahuas, ranking LayerCAM, Score-CAM, and IS-CAM highest when compared to crowdsourced choices via RBO.