Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
How do you (in simple theory) calculate the receptive input field of a certain cell in a feature map in a convolutional neural network?
Counting backwards from the feature layer to the input layer, each layer increases the receptive field size by the kernel size.