most citedBayesian Fusion for Infrared and Visible Images

163 citations · 230 across the 6 of their papers we have counts for

collaborators

10 papers

cs.CV20212 cited

Deep Convolutional Sparse Coding Network for Pansharpening with Guidance of Side Information

Shuang Xu, Jiangshe Zhang, Kai Sun +4

Pansharpening is a fundamental issue in remote sensing field. This paper proposes a side information partially guided convolutional sparse coding (SCSC) model for pansharpening. Th…

cs.CV2021

Deep Gradient Projection Networks for Pan-sharpening

Shuang Xu, Jiangshe Zhang, Zixiang Zhao +3

Pan-sharpening is an important technique for remote sensing imaging systems to obtain high resolution multispectral images. Recently, deep learning has become the most popular tool…

cs.CV20202 cited

Domain Adaptive Object Detection via Feature Separation and Alignment

Chengyang Liang, Zixiang Zhao, Junmin Liu +1

Recently, adversarial-based domain adaptive object detection (DAOD) methods have been developed rapidly. However, there are two issues that need to be resolved urgently. Firstly, n…

cs.CV2020

MFIF-GAN: A New Generative Adversarial Network for Multi-Focus Image Fusion

Yicheng Wang, Shuang Xu, Junmin Liu +3

Multi-Focus Image Fusion (MFIF) is a promising image enhancement technique to obtain all-in-focus images meeting visual needs and it is a precondition of other computer vision task…

eess.IV2020

When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method

Zixiang Zhao, Jiangshe Zhang, Shuang Xu +3

Infrared and visible image fusion, as a hot topic in image processing and image enhancement, aims to produce fused images retaining the detail texture information in visible images…

eess.IV20207 cited

Deep Convolutional Sparse Coding Networks for Image Fusion

Shuang Xu, Zixiang Zhao, Yicheng Wang +3

Image fusion is a significant problem in many fields including digital photography, computational imaging and remote sensing, to name but a few. Recently, deep learning has emerged…