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Multi-modality image fusion is a technique that combines information from different sensors or modalities, enabling the fused image to retain complementary features from each modality, such as functional highlights and texture details.
Deep convolutional sparse coding networks for image fusion
Shuang Xu, Zixiang Zhao, Yicheng Wang, Chunxia Zhang, Junmin Liu, and Jiangshe Zhang · 2005
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Medical image fusion: A survey of the state of the art
Alex Pappachen James and Belur V. Dasarathy · 2014
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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Densefuse: A fusion approach to infrared and visible images
Hui Li and Xiao-Jun Wu · 2018
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A survey on region based image fusion methods
Bikash Meher, Sanjay Agrawal, Rutuparna Panda, and Ajith Abraham · 2019
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Yolov4: Optimal speed and accuracy of object detection
Alexey Bochkovskiy, Chien-Yao Wang, and Hong-Yuan Mark Liao · 2020
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ultralytics/yolov5
Glenn Jocher · 2020
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Unsupervised deep image fusion with structure tensor representations
Hyungjoo Jung, Youngjung Kim, Hyunsung Jang, Namkoo Ha, and Kwanghoon Sohn · 2020
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Mdlatlrr: A novel decomposition method for infrared and visible image fusion
Hui Li, Xiao-Jun Wu, and Josef Kittler · 2020
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DIDFuse: Deep image decomposition for infrared and visible image fusion
Zixiang Zhao, Shuang Xu, Chunxia Zhang, Junmin Liu, Jiangshe Zhang, and Pengfei Li · 2020
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Equivariant imaging: Learning beyond the range space
Dongdong Chen, Julián Tachella, and Mike E. Davies · 2021
Cited alongside, same era.
Deep convolutional neural network for multi-modal image restoration and fusion
Xin Deng and Pier Luigi Dragotti · 2021
Cited alongside, same era.
Rfn-nest: An end-to-end residual fusion network for infrared and visible images
Hui Li, Xiao-Jun Wu, and Josef Kittler · 2021
Cited alongside, same era.
Searching a hierarchically aggregated fusion architecture for fast multi-modality image fusion
Risheng Liu, Zhu Liu, Jinyuan Liu, and Xin Fan · 2021
Cited alongside, same era.
Sdnet: A versatile squeeze-and-decomposition network for real-time image fusion
Hao Zhang and Jiayi Ma · 2021
Cited alongside, same era.
Robust equivariant imaging: a fully unsupervised framework for learning to image from noisy and partial measurements
Detfusion: A detection-driven infrared and visible image fusion network
Yiming Sun, Bing Cao, Pengfei Zhu, and Qinghua Hu · 2022
Later among the works it cites.
Image fusion transformer
Vibashan Vs, Jeya Maria Jose Valanarasu, Poojan Oza, and Vishal M Patel · 2022
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Unsupervised misaligned infrared and visible image fusion via cross-modality image generation and registration
Di Wang, Jinyuan Liu, Xin Fan, and Risheng Liu · 2022
Later among the works it cites.
Restormer: Efficient transformer for high-resolution image restoration
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang · 2022
Later among the works it cites.
Imaging with equivariant deep learning: From unrolled network design to fully unsupervised learning
Dongdong Chen, Mike E. Davies, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Ferdia Sherry, and Julián Tachella · 2023
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Dongdong Chen, Julián Tachella, and Mike E. Davies · 2022
Cited alongside, same era.
Multi-modal convolutional dictionary learning
Fangyuan Gao, Xin Deng, Mai Xu, Jingyi Xu, and Pier Luigi Dragotti · 2022
Cited alongside, same era.
Reconet: Recurrent correction network for fast and efficient multi-modality image fusion
Zhanbo Huang, Jinyuan Liu, Xin Fan, Risheng Liu, Wei Zhong, and Zhongxuan Luo · 2022
Cited alongside, same era.
Towards all weather and unobstructed multi-spectral image stitching: Algorithm and benchmark
Zhiying Jiang, Zengxi Zhang, Xin Fan, and Risheng Liu · 2022
Cited alongside, same era.
Fusion from decomposition: A self-supervised decomposition approach for image fusion
Pengwei Liang, Junjun Jiang, Xianming Liu, and Jiayi Ma · 2022
Cited alongside, same era.
Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection
Jinyuan Liu, Xin Fan, Zhanbo Huang, Guanyao Wu, Risheng Liu, Wei Zhong, and Zhongxuan Luo · 2022
Cited alongside, same era.
http://www.med.harvard.edu/AANLIB/home.html
Harvard Medical website
Cited in the paper.
Lrrnet: A novel representation learning guided fusion network for infrared and visible images
Hui Li, Tianyang Xu, Xiaojun Wu, Jiwen Lu, and Josef Kittler · 2023
Closest in time.
Sensing theorems for unsupervised learning in linear inverse problems
Julián Tachella, Dongdong Chen, and Mike Davies · 2023
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MURF: mutually reinforcing multi-modal image registration and fusion
Han Xu, Jiteng Yuan, and Jiayi Ma · 2023
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Lfienet: Light field image enhancement network by fusing exposures of lf-dslr image pairs
Wuyang Ye, Tao Yan, Jiahui Gao, and Yang Yang · 2023
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Visible and infrared image fusion using deep learning
Xingchen Zhang and Yiannis Demiris · 2023
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Glgnet: light field angular superresolution with arbitrary interpolation rates
Li Fang, Qian Wang, and Long Ye · 2024
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