PixelShuffle

• Conv filters with a stride of $1/s$ to scale up 1D signals by a factor of s.
• Only the weights that lie exactly on positions are used to create the outputs, and the ones that fall between positions are discarded.
• This can be implemented by multiplying the number of channels in the kernel by a factor of s, where the sth output position is computed from just the sth subset of channels.
• This can be trivially extended to 2D convolution, which requires s2 channels