Image Attribution on CUB-200-2011

Metric: Insertion AUC score (ResNet-101) (higher is better)

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#	Model↕	Insertion AUC score (ResNet-101)▼	Extra Data	Paper	Date↕	Code
1	SMDL-Attribution (ICLR version)	0.7262	No	Less is More: Fewer Interpretable Region via Sub...	2024-02-14	Code
2	Grad-CAM	0.7224	No	Grad-CAM: Visual Explanations from Deep Networks...	2016-10-07	Code
3	RISE	0.7193	No	RISE: Randomized Input Sampling for Explanation ...	2018-06-19	Code
4	HSIC-Attribution	0.6843	No	Making Sense of Dependence: Efficient Black-box ...	2022-06-13	Code
5	LIME	0.6812	No	"Why Should I Trust You?": Explaining the Predic...	2016-02-16	Code
6	Kernel SHAP	0.6763	No	A Unified Approach to Interpreting Model Predict...	2017-05-22	Code
7	Saliency	0.6585	No	Deep Inside Convolutional Networks: Visualising ...	2013-12-20	Code
8	Integrated Gradients	0.0422	No	Axiomatic Attribution for Deep Networks	2017-03-04	Code

#1SMDL-Attribution (ICLR version)SOTA
0.7262
Insertion AUC score (ResNet-101)· 2024-02-14
Less is More: Fewer Interpretable Region via Submodular Subset Selection Code
#2Grad-CAMSOTA
0.7224
Insertion AUC score (ResNet-101)· 2016-10-07
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Code
#3RISE
0.7193
Insertion AUC score (ResNet-101)· 2018-06-19
RISE: Randomized Input Sampling for Explanation of Black-box Models Code
#4HSIC-Attribution
0.6843
Insertion AUC score (ResNet-101)· 2022-06-13
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure Code
#5LIMESOTA
0.6812
Insertion AUC score (ResNet-101)· 2016-02-16
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Code
#6Kernel SHAP
0.6763
Insertion AUC score (ResNet-101)· 2017-05-22
A Unified Approach to Interpreting Model Predictions Code
#7SaliencySOTA
0.6585
Insertion AUC score (ResNet-101)· 2013-12-20
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Code
#8Integrated Gradients
0.0422
Insertion AUC score (ResNet-101)· 2017-03-04
Axiomatic Attribution for Deep Networks Code