图像融合|基于深度学习的多曝光图像融合(Multi-exposure Image Fusion)论文及代码整理 Paper下载|计算机视觉|神经网络

基于深度学习的多曝光图像融合(Multi-exposure Image Fusion)论文及代码整理首先附上近期整理基于深度学习的图像融合论文的思维导图

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【图像融合|基于深度学习的多曝光图像融合(Multi-exposure Image Fusion)论文及代码整理】本篇博客主要整理基于深度学习的多曝光图像融合的论文和代码
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基于卷积神经网络的图像融合框架 1. DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme Exposure Image Pairs [DeepFuse(ICCV 2017)] [Paper] [Code]
2. Multi-exposure fusion with CNN features [CNN(ICIP 2018)] [Paper] [Code]
3. Deep guided learning for fast multi-exposure image fusion [DeepFuse(MEF-Net(TIP 2020))] [Paper] [Code]
4. Multi-exposure high dynamic range imaging with informative content enhanced network [ICEN(NC 2020)] [Paper]
5. Deep coupled feedback network for joint exposure fusion and image super-resolutions [CF-Net(TIP 2021)] [Paper] [Code]
6. Deep unsupervised learning based on color un-referenced loss functions for multi-exposure image fusion [UMEF(IF 2021)] [Paper] [Code]
7. Automatic Intermediate Generation With Deep Reinforcement Learning for Robust Two-Exposure Image Fusion [DRLF(TNNLS 2021)] [Paper]
8. DMulti-exposure image fusion via deep perceptual enhancement [DPE-MEF(IF 2022)] [Paper] [Code]
9. TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework using Self-Supervised Multi-Task Learning [TransMEF(AAAI 2022)] [Paper] [Code]
基于生成对抗网络的图像融合框架 1. MEF-GAN: Multi-Exposure Image Fusion via Generative Adversarial Networks [MEF-GAN(TIP 2020)] [Paper] [Code]
2. Two exposure fusion using prior-aware generative adversarial network [PA-GAN(TMM 2021)] [Paper]
3. Attention-guided Global-local Adversarial Learning for Detail-preserving Multi-exposure Image Fusion [AGAL(TCSVT 2021)] [Paper] [Code]
4. GANFuse: a novel multi-exposure image fusion method based on generative adversarial networks [GANFuse(NCAA 2021)] [Paper]
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