Abstract: This paper proposes a new convolution layer implementation method for the parallel computation of high-dimensional matrices. It can accomplish global convolution or local convolution by ...

Abstract: Many imaging applications require the implementation of space-varying convolution for accurate restoration and reconstruction of images. Here, we use the term space-varying convolution to ...

A research team from the University of California San Diego and Microsoft has come up with a novel approach to improve model accuracy on computer vision tasks at extremely low compute costs, achieving ...

Recent research in dynamic convolution shows substantial performance boost for efficient CNNs, due to the adaptive aggregation of K static convolution kernels.It has two limitations: (a) it increases ...

Currently, only 4-D input tensors (batched image-like tensors) are supported. unfoldNd implements the operation for 3d and 5d inputs and shows good performance. Like torch.nn.Fold, but supports 3d, 4d ...