Active Convolution
Active Convolution
An **Active Convolution** is a type of [convolution](https://paperswithcode.com/method/convolution) which does not have a fixed shape of the receptive field, and can be used to take more diverse forms of receptive fields for convolutions. Its shape can be learned through backpropagation during training. It can be seen as a generalization of convolution; it can define not only all conventional convolutions, but also convolutions with fractional pixel coordinates. We can freely change the shape of the convolution, which provides greater freedom to form CNN structures. Second, the shape of the convolution is learned while training and there is no need to tune it by hand
Active Convolution: Learning the Shape of Convolution for Image Classification
https://paperswithcode.com/paper/active-convolution-learning-the-shape-of
Active Convolution: Learning the Shape of Convolution for Image Classification