Scaling Up Your Kernels to 31×31: Revisiting Large Kernel Design in CNNs

We revisit large kernel design in modern convolutional neural networks (CNNs). Inspired by recent advances in vision transformers (ViTs), in this paper, we demonstrate that using a few large convolutional kernels instead of a stack of small kernels could be a more powerful paradigm. We suggested fiv... View More