Lightweight group convolutional network for single image super-resolution.

•A novel CNN-based SISR method with cascaded modules named Lightweight Group Convolution Network (LGCN) is proposed.•The paper develops a Memory Group Convolutional Network (MGCN), which uses group convolution as the convolutional layer to reduce the network parameters.•The paper develops a novel channel attention method for SISR in MGCN, which replaces the fully connection layer with 1  ×  1 convolutional layer based on the idea of squeeze and excitation net.•Extensive experiments on benchmark datasets show our LGCN model achieves competitive results against state-of-the-art methods on both accuracy and speed.