IEEE

Superpixel Guided Deformable Convolution Network for Hyperspectral Image Classification

Abstract: Convolutional neural networks are widely used in the field of hyperspectral image classification because of their excellent nonlinear feature extraction ability. However, as the sampling ...
IEEE

KNLConv: Kernel-Space Non-Local Convolution for Hyperspectral Image Super-Resolution

Abstract: Pixel-level adaptive convolution, which overcomes the deficiency of the spatial-invariance of standard convolution, is always limited to performing feature extraction from local patches and ...
GitHub

Virtual Sparse Convolution for Multimodal 3D Object Detection

VirConv-L: A light-weight multimodal 3D detector based on Virtual Sparse Convolution. VirConv-T: A improved multimodal 3D detector based on Virtual Sparse Convolution and transformed refinement scheme ...
GitHub

ESC: Emulating Self-attention with Convolution for Efficient Image Super-Resolution

In this paper, we tackle the high computational overhead of transformers for lightweight image super-resolution. (SR). Motivated by the observations of self-attention's inter-layer repetition, we ...