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
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
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基于卷积神经网络的图像融合框架
1. Multi-focus image fusion with a deep convolutional neural network [CNN(IF 2017)] [Paper] [Code]
2. Ensemble of CNN for multi-focus image fusion [ECNN(IF 2019)] [Paper] [Code]
3. Multilevel features convolutional neural network for multifocus image fusion [MLFCNN(TCI 2019)] [Paper]
4. DRPL: Deep Regression Pair Learning for Multi-Focus Image Fusion [DRPL(TIP 2020)] [Paper] [Code]
5. An α-Matte Boundary Defocus Model-Based Cascaded Network for Multi-Focus Image Fusion [MMF-Net(TIP 2020)] [Paper] [Code]
6. Towards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy [MFF-SSIM(TCI 2020)] [Paper] [Code]
7. Structural Similarity Loss for Learning to Fuse Multi-Focus Images [MFNet(Sensors 2020)] [Paper]
8. Global-Feature Encoding U-Net (GEU-Net) for Multi-Focus Image Fusion [GEU-Net(TIP 2021)] [Paper] [Code]
9. DTMNet: A Discrete Tchebichef Moments-Based Deep Neural Network for Multi-Focus Image Fusion [DTMNet(ICCV 2021)] [Paper]
10. SMFuse: Multi-Focus Image Fusion Via Self-Supervised Mask-Optimization [SMFuse(TCI 2021)] [Paper] [Code]
11. Depth-Distilled Multi-focus Image Fusion [D2MFIF(TMM 2021)] [Paper] [Code]
12. SESF-Fuse: an unsupervised deep model for multi-focus image fusion [SESF-Fuse(NCAA 2021)] [Paper] [Code]
基于生成对抗网络的图像融合框架
1. FuseGAN: Learning to fuse multi-focus image via conditional generative adversarial network [FuseGAN(TMM 2019)] [Paper]
2. A generative adversarial network with adaptive constraints for multi-focus image fusion [ACGAN(NCA 2020)] [Paper] [Code]
3. MFF-GAN: An unsupervised generative adversarial network with adaptive and gradient joint constraints for multi-focus image fusion [MFF-GAN(IF 2021)] [Paper] [Code]
4. MFIF-GAN: A new generative adversarial network for multi-focus image fusion [MFIF-GAN(SPIC 2021)] [Paper] [Code]
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