Gradient ascent on class scores and input-image gradients produce visualizations of ConvNet class notions and saliency maps usable for weakly supervised segmentation.
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Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Gradient ascent on class scores and input-image gradients produce visualizations of ConvNet class notions and saliency maps usable for weakly supervised segmentation.