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

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

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
图像融合系列博客还有：

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2. 图像融合综述论文整理参见：图像融合综述论文整理
3. 图像融合评估指标参见：红外和可见光图像融合评估指标
4. 图像融合常用数据集整理参见：图像融合常用数据集整理
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7. 更加详细的红外和可见光图像融合代码参见：红外和可见光图像融合论文及代码整理
8. 基于深度学习的多曝光图像融合论文及代码整理参见：基于深度学习的多曝光图像融合论文及代码整理
9. 基于深度学习的多聚焦图像融合论文及代码整理参见：基于深度学习的多聚焦图像融合(Multi-focus Image Fusion)论文及代码整理
10. 基于深度学习的全色图像锐化论文及代码整理参见：基于深度学习的全色图像锐化(Pansharpening)论文及代码整理
11. 基于深度学习的医学图像融合论文及代码整理参见：基于深度学习的医学图像融合(Medical image fusion)论文及代码整理
12. 彩色图像融合参见: 彩色图像融合
13. SeAFusion:首个结合高级视觉任务的图像融合框架参见：SeAFusion:首个结合高级视觉任务的图像融合框架

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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