LDConv: Linear deformable convolution for improving convolutional neural networks

Neural networks based on convolutional operations have achieved remarkable results in the field of deep learning, but there are two inherent flaws in standard convolutional operations. On the one hand, the convolution operation is confined to a local window, so it cannot capture information from other locations, and its sampled shapes is fixed. On the other hand, the size of the convolutional kernel is fixed to k × k, which is a fixed square shape, and the number of parameters tends to grow squarely with size. Although Deformable Convolution (Deformable Conv) address the problem of fixed sampling of standard convolutions, the number of parameters also tends to grow in a squared manner, and Deformable Conv do…

• CN
  Chongqing Normal University

  Award: 21XLB035
• NS
  Natural Science Foundation of Chongqing

  Award: CSTB2022NSCQ-MSX1200
• CM
  Chongqing Municipal Education Commission

  Awards: KJZD-M202300502, KJQN20220-0537