Explainable CNNs
XGrad-CAM
Introduced by Fu et al. in Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNsXGrad-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 CNNs
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Image Generation | 1 | 33.33% |
| Edge Detection | 1 | 33.33% |
| Saliency Detection | 1 | 33.33% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
