activity
20202023
most citedCross Aggregation Transformer for Image Restoration

122 citations · 294 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2023★ 30 cited

Hierarchical Integration Diffusion Model for Realistic Image Deblurring

Zheng Chen, Yulun Zhang, Ding Liu +4

Diffusion models (DMs) have recently been introduced in image deblurring and exhibited promising performance, particularly in terms of details reconstruction. However, the diffusio…

cs.CV2023★ 9 cited

Binarized Spectral Compressive Imaging

Yuanhao Cai, Yuxin Zheng, Jing Lin +3

Existing deep learning models for hyperspectral image (HSI) reconstruction achieve good performance but require powerful hardwares with enormous memory and computational resources.…

cs.CV2023★ 51 cited

Universal Domain Adaptation for Remote Sensing Image Scene Classification

Qingsong Xu, Yilei Shi, Xin Yuan +1

The domain adaptation (DA) approaches available to date are usually not well suited for practical DA scenarios of remote sensing image classification, since these methods (such as…

cs.CV2022★ 122 cited

Cross Aggregation Transformer for Image Restoration

Zheng Chen, Yulun Zhang, Jinjin Gu +3

Recently, Transformer architecture has been introduced into image restoration to replace convolution neural network (CNN) with surprising results. Considering the high computationa…

cs.CV2022★ 47 cited

Accurate Image Restoration with Attention Retractable Transformer

Jiale Zhang, Yulun Zhang, Jinjin Gu +3

Recently, Transformer-based image restoration networks have achieved promising improvements over convolutional neural networks due to parameter-independent global interactions. To…

cs.CV2022★ 5 cited

Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstruction

Yuanhao Cai, Jing Lin, Xiaowan Hu +5

Many algorithms have been developed to solve the inverse problem of coded aperture snapshot spectral imaging (CASSI), i.e., recovering the 3D hyperspectral images (HSIs) from a 2D…

eess.IV2022★ 13 cited

HDNet: High-resolution Dual-domain Learning for Spectral Compressive Imaging

Xiaowan Hu, Yuanhao Cai, Jing Lin +5

The rapid development of deep learning provides a better solution for the end-to-end reconstruction of hyperspectral image (HSI). However, existing learning-based methods have two…

eess.IV2021

Modeling Mask Uncertainty in Hyperspectral Image Reconstruction

Jiamian Wang, Yulun Zhang, Xin Yuan +2

Recently, hyperspectral imaging (HSI) has attracted increasing research attention, especially for the ones based on a coded aperture snapshot spectral imaging (CASSI) system. Exist…

eess.IV2021★ 15 cited

Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction

Yuanhao Cai, Jing Lin, Xiaowan Hu +5

Hyperspectral image (HSI) reconstruction aims to recover the 3D spatial-spectral signal from a 2D measurement in the coded aperture snapshot spectral imaging (CASSI) system. The HS…

cs.CV2020★ 2 cited

Spatial--spectral FFPNet: Attention-Based Pyramid Network for Segmentation and Classification of Remote Sensing Images

Qingsong Xu, Xin Yuan, Chaojun Ouyang +1

We consider the problem of segmentation and classification of high-resolution and hyperspectral remote sensing images. Unlike conventional natural (RGB) images, the inherent large…