In a CNN the image sizes get reduced through valid convolutions and padding layers (while the depth increases). In popular NN, e.g. VGG16 it goes down to (7x7x512) (width x height x depth). Would it be problematic to reduce the dimension even further to 1×1 (width x height) or when can this be beneficial? Unfortunately, I couldn’t find anything related to the question online.