Pinned
There is something deeply unsatisfying in strided convolutional layers in virtually all CNNs. The stride=2 convolutions use kernel_size=3 and padding=1. The feature maps have sizes that are power of 2. As a result, the borders are treated differently and there is asymmetry.
