Grid Saliency for Context Explanations of Semantic Segmentation

Lukas Hoyer, Mauricio Munoz, Prateek Katiyar, Anna Khoreva, Volker Fischer

Neural Information Processing Systems 

Recently,there has been agrowing interest in developing saliencymethods that providevisualexplanations ofnetworkpredictions. Still,theusability ofexisting methods is limited to image classification models. To overcome this limitation, we extend the existing approaches to generategrid saliencies, which provide spatially coherent visualexplanations for(pixel-level)denseprediction networks.

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