Pooling Revisited: Your Receptive Field is Suboptimal

receptive fields are how CNNs see objects

DynOPool applicable to most operations that control size of receptive field

related works

NAS: generic, not designed for feature map size optimization
dynamic kernel shape: changing filter size
Shape Adaptor: directly learn feature map size
- only handles symmetric feature maps and selects a predefined resizing ration range
DiffStride: spectral pooling to determine optimal scale factor of pooling layer
- implement downsampling with cropping in the frequency domain

DynOPool

differentiable pooling layer
- scaling factor for horizontal and vertical directions to be optimized
- find four query points in each grid
- derive output feature via max pooling of these query points
optimization requires additional work because of rounding function
- output size width and height must be integers
- optimization by relaxation
- regularization for computational complexity in addition to task loss
shown to also be compatible with NAS, semantic segmentation, etc.