HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions. (arXiv:2207.14284v2 [cs.CV] UPDATED)

Recent progress in vision Transformers exhibits great success in various
tasks driven by the new spatial modeling mechanism based on dot-product
self-attention. In this paper, we show that the key ingredients behind the
vision Transformers, namely input-adaptive, long-range and high-order spatial
interactions, can also be efficiently implemented with a convolution-based
framework. We present the Recursive Gated Convolution
($\textit{g}^\textit{n}$Conv) that performs high-order spatial interactions
with gated convolutions and recursive designs. The new operation is highly
flexible and customizable, which is compatible …

arxiv cv hornet interactions recursive