DiffGradCAM and DiffGradCAM++ use logit differences for contrastive class activation maps that resist passive fooling while matching GradCAM outputs in clean cases, tested with a new SHAM benchmark on multi-class tasks.
Ablation-cam: Visual explanations for deep convo- lutional network via gradient-free localization
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DiffGradCAM: A Class Activation Map Using the Full Model Decision to Solve Unaddressed Adversarial Attacks
DiffGradCAM and DiffGradCAM++ use logit differences for contrastive class activation maps that resist passive fooling while matching GradCAM outputs in clean cases, tested with a new SHAM benchmark on multi-class tasks.