Convolutional Neural Networks

DiCENet is a convolutional neural network architecture that utilizes dimensional convolutions (and dimension-wise fusion). The dimension-wise convolutions apply light-weight convolutional filtering across each dimension of the input tensor while dimension-wise fusion efficiently combines these dimension-wise representations; allowing the DiCE Unit in the network to efficiently encode spatial and channel-wise information contained in the input tensor.

Source: DiCENet: Dimension-wise Convolutions for Efficient Networks


Paper Code Results Date Stars


Component Type
DiCE Unit
Image Model Blocks