I(x, y, no of channels) is the image, and Fi(x, y, no of filters ) is the feature map at some layer 'i'. Given the architecture of a Convolutional Neural Network like VGGNet and a feature map after a certain layer Fi, is there an efficient way to find which pixels of the input image I, that contribute to a location in the feature map? I will want to implement this in python.