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Status: Unchecked ×Keyword: convolution ×Clear all

2 claims from 1 paper

1. Computer Science › Advanced Neural Network Applications

   On the Integration of Self-Attention and Convolution

   Pan, Ge, Lü et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 2022

   The paper argues that convolution and self-attention share the same core operation, and uses this to build ACmix, a mixed model that reports improved image recognition results with little extra computation.

   Unchecked2 claims
   Show 2 claims

   1. UncheckedThe paper states that a standard k x k convolution can be split into k^2 separate 1x1 convolutions, followed by shift and summation steps.“Specifically, we first show that a traditional convolution with kernel size k x k can be decomposed into k^2 individual 1x1 convolutions, followed by shift and summation operations.”
   2. UncheckedThe authors report that their mixed model, ACmix, gives consistently better results than competitive baselines on image recognition and downstream tasks.“Extensive experiments show that our model achieves consistently improved results over competitive baselines on image recognition and downstream tasks.”