IEEE

Learning a 3-D-CNN and Convolution Transformers for Hyperspectral Image Classification

Abstract: Hyperspectral image (HSI) classification is an important but challenging task. Conventional convolutional neural networks (CNNs) are able to extract local spectral spatial features but ...
IEEE

RefConv: Reparameterized Refocusing Convolution for Powerful ConvNets

Abstract: We propose reparameterized refocusing convolution (RefConv) as a replacement for regular convolutional layers, which is a plug-and-play module to improve the performance without any ...
GitHub

[AAAI 2026]Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection

Offical implementation of "Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection" we also add our config in https://github.com/zcablii/LSKNet and ...
GitHub

Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation

LiDAR point cloud semantic segmentation enables the robots to obtain fine-grained semantic information of the surrounding environment. Recently, many works project the point cloud onto the 2D image ...