activity
20182022
most citedDIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion

328 citations · 706 across the 19 of their papers we have counts for

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11 papers · 1 filter

cs.CV2022★ 24 cited

CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion

Zixiang Zhao, Haowen Bai, Jiangshe Zhang +5

Multi-modality (MM) image fusion aims to render fused images that maintain the merits of different modalities, e.g., functional highlight and detailed textures. To tackle the chall…

cs.CV2022★ 11 cited

MSSPN: Automatic First Arrival Picking using Multi-Stage Segmentation Picking Network

Hongtao Wang, Jiangshe Zhang, Xiaoli Wei +4

Picking the first arrival times of prestack gathers is called First Arrival Time (FAT) picking, which is an indispensable step in seismic data processing, and is mainly solved manu…

cs.CV2021★ 13 cited

Discrete Cosine Transform Network for Guided Depth Map Super-Resolution

Zixiang Zhao, Jiangshe Zhang, Shuang Xu +2

Guided depth super-resolution (GDSR) is an essential topic in multi-modal image processing, which reconstructs high-resolution (HR) depth maps from low-resolution ones collected wi…

cs.CV2021★ 2 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.CV2020★ 52 cited

Towards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy

Shuang Xu, Lizhen Ji, Zhe Wang +4

Multi-focus image fusion (MFF) is a popular technique to generate an all-in-focus image, where all objects in the scene are sharp. However, existing methods pay little attention to…

cs.CV2020★ 2 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★ 4 cited

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…

cs.CV2020★ 163 cited

Bayesian Fusion for Infrared and Visible Images

Zixiang Zhao, Shuang Xu, Chunxia Zhang +2

Infrared and visible image fusion has been a hot issue in image fusion. In this task, a fused image containing both the gradient and detailed texture information of visible images…

cs.CV2020★ 6 cited

Efficient and Model-Based Infrared and Visible Image Fusion Via Algorithm Unrolling

Zixiang Zhao, Shuang Xu, Jiangshe Zhang +3

Infrared and visible image fusion (IVIF) expects to obtain images that retain thermal radiation information from infrared images and texture details from visible images. In this pa…

cs.CV2020★ 56 cited

MFFW: A new dataset for multi-focus image fusion

Shuang Xu, Xiaoli Wei, Chunxia Zhang +2

Multi-focus image fusion (MFF) is a fundamental task in the field of computational photography. Current methods have achieved significant performance improvement. It is found that…