Oct 19, 2023 · One promising approach to address this issue is group convolution, which effectively reduces the computational cost by grouping channels.

Oct 20, 2023 · Abstract. The performance of neural networks has been significantly improved by in- creasing the number of channels in convolutional layers.

This paper mathematically analyzes the approximation of the group convolution to the standard convolution with respect to the number of groups and proposes ...

Advanced deep models achieve accurate flow estimation often with a considerable computation complexity and time-consuming training processes. In this work, we ...

We provide experimental results that validate our theoretical findings and demonstrate the superior performance of the balanced group convolution over other ...

In this paper, we propose a new convolution methodology called “two-level” group convolution that is robust with respect to the increase of the number of groups ...

Balanced Group Convolution: An Improved Group Convolution Based on Approximability Estimates. Y Lee, J Park, CO Lee. arXiv preprint arXiv:2310.12461, 2023.

Balanced Group Convolution: An Improved Group Convolution Based on Approximability Estimates ... This is a preprint. See "About preprints" page for more details.

Furthermore, we propose a novel variant of the group convolution called balanced group convolution, which shows a higher approximation with a small additional ...

We provide experimental results that validate our theoretical findings and demonstrate the superior performance of the balanced group convolution over other ...