Scaling Up Your Kernels: Large Kernel Design in ConvNets towards
Universal Representations
Scaling Up Your Kernels: Large Kernel Design in ConvNets towards
Universal Representations
This paper proposes the paradigm of large convolutional kernels in designing modern Convolutional Neural Networks (ConvNets). We establish that employing a few large kernels, instead of stacking multiple smaller ones, can be a superior design strategy. Our work introduces a set of architecture design guidelines for large-kernel ConvNets that optimize …