XGrad-CAM, or Axiom-based Grad-CAM, is a class-discriminative visualization method and able to highlight the regions belonging to the objects of interest. Two axiomatic properties are introduced in the derivation of XGrad-CAM: Sensitivity and Conservation. In particular, the proposed XGrad-CAM is still a linear combination of feature maps, but able to meet the constraints of those two axioms.
Source: Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNsPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Image Generation | 1 | 33.33% |
Edge Detection | 1 | 33.33% |
Saliency Detection | 1 | 33.33% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |