ConvMLP

ConvMLP is a hierarchical convolutional MLP for visual recognition, which consists of a stage-wise, co-design of convolution layers, and MLPs. The Conv Stage consists of $C$ convolutional blocks with $1\times 1$ and $3\times 3$ kernel sizes. It is repeated $M$ times before a down convolution is utilized to express a level $L$. The MLP-Conv Stage consists of Channelwise MLPs, with skip layers, and a depthwise convolution. This is repeated $M$ times before a down convolution is utilized to express a level $\mathcal{L}$.