图像融合论文baseline及其网络模型

目录论文均为【顶会】【顶刊】或者【高被引】,尚未完成,待完善

加的代表已有阅读笔记

文章目录

  • 2017
    • DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme Exposure Image Pairs
  • 2019
    • DenseFuse: A Fusion Approach to Infrared and Visible Images
    • FusionGAN: A generative adversarial network for infrared and visible image fusion
  • 2020
    • (PMGI)Rethink- ing the image fusion: A fast unified image fusion network based on proportional mainte- nance of gradient and intensity
    • U2Fusion: A Unified Unsupervised Image Fusion Network
    • IFCNN: A general image fusion framework based on convolutional neural network
    • DDcGAN: A Dual-discriminator Conditional Generative Adversarial Network for Multi-resolution Image Fusion
    • DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion
  • 2021
    • GANMcC: A Generative Adversarial Network With Multiclassification Constraints for Infrared and Visible Image Fusion
    • (MFEIF)Learning a Deep Multi-Scale Feature Ensemble and an Edge-Attention Guidance for Image Fusion
    • RFN-Nest: An end-to-end residual fusion network for infrared and visible images
    • SDNet: A Versatile Squeeze-and-Decomposition Network for Real-Time Image Fusion
  • 2022
    • (DeFusion)Fusion from decomposition: A self-supervised decomposition approach for image fusion
    • ReCoNet: Recurrent Correction Network for Fast and Efficient Multi-modality Image Fusion
    • PIAFusion: A progressive infrared and visible image fusion network based on illumination aware
    • SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer
  • 2023
    • LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images
    • CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion
    • CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion
  • 传送门
    • 图像融合相关论文阅读笔记
    • 图像融合论文baseline总结
    • 其他论文
    • 其他总结
    • ✨精品文章总结

2017

DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme Exposure Image Pairs

笔记链接

图像融合论文baseline及其网络模型_第1张图片


2019

DenseFuse: A Fusion Approach to Infrared and Visible Images

笔记链接

  • CBF, JSR, GTF, JSRSD, CNN, DeepFuse
    图像融合论文baseline及其网络模型_第2张图片

FusionGAN: A generative adversarial network for infrared and visible image fusion

笔记链接

  • ASR,CVT,DTCWT,FPDE,GFF,LPP,TSIFVS,GTF
    图像融合论文baseline及其网络模型_第3张图片

2020

(PMGI)Rethink- ing the image fusion: A fast unified image fusion network based on proportional mainte- nance of gradient and intensity

笔记链接

  • LPP (Toet 1989),
  • GTF (Ma et al.2016)
  • DDLatLRR (Li and Wu 2018a)
  • LatLRR (Li and Wu2018b)
  • FusionGAN
    图像融合论文baseline及其网络模型_第4张图片

U2Fusion: A Unified Unsupervised Image Fusion Network

笔记链接

  • VIF
    • HMSD , GTF, DenseFuse, FusionGAN, DDcGAN
  • PET-MRI
    • RPCNN, CNN,PAPCNN, NSCT
  • 多曝光
    • GFF [46], DSIFT, GBM, Deepfuse, FLER
  • 多聚焦
    • DSIFT, GBM, CNN, GFDF, SESF-Fuse
      图像融合论文baseline及其网络模型_第5张图片

IFCNN: A general image fusion framework based on convolutional neural network

笔记链接

  • GFF,LPSR,MFCNN,MECNN
    图像融合论文baseline及其网络模型_第6张图片

DDcGAN: A Dual-discriminator Conditional Generative Adversarial Network for Multi-resolution Image Fusion

笔记链接

  • directional discrete cosine transform and principal component analysis (DDCTPCA)
  • hybrid multi-scale decomposition (HMSD)
  • fourth-order partial differential equations (FPDE)
  • gradient transfer fusion(GTF)
  • different resolution total variation (DRTV)
  • DenseFuse
  • FusionGAN

图像融合论文baseline及其网络模型_第7张图片

DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion

笔记链接

  • FusionGAN,DenseFuse,ImageFuse,DeepFuse,TSIFVS, TVADMM,CSR, ADF

图像融合论文baseline及其网络模型_第8张图片


2021

GANMcC: A Generative Adversarial Network With Multiclassification Constraints for Infrared and Visible Image Fusion

笔记链接

  • LPP, LP,CVT ,DTCWT,GTF,CNN,FusionGAN

图像融合论文baseline及其网络模型_第9张图片

(MFEIF)Learning a Deep Multi-Scale Feature Ensemble and an Edge-Attention Guidance for Image Fusion

  • 笔记链接
  • CBF, GTF, JSRSD, DRTV, FPDE, FusionGAN, DDcGAN

图像融合论文baseline及其网络模型_第10张图片

RFN-Nest: An end-to-end residual fusion network for infrared and visible images

图像融合论文baseline及其网络模型_第11张图片

SDNet: A Versatile Squeeze-and-Decomposition Network for Real-Time Image Fusion

笔记链接

  • ASR, PCA, NSCT, CNN, GTF, MDLatLRR, DenseFuse, FusionGAN, U2Fusion
    图像融合论文baseline及其网络模型_第12张图片

2022

(DeFusion)Fusion from decomposition: A self-supervised decomposition approach for image fusion

图像融合论文baseline及其网络模型_第13张图片

ReCoNet: Recurrent Correction Network for Fast and Efficient Multi-modality Image Fusion

图像融合论文baseline及其网络模型_第14张图片

PIAFusion: A progressive infrared and visible image fusion network based on illumination aware

笔记链接

  • two traditional methods, i.e.
    • GTF, MDLatLRR,
  • three AE-based method, i.e.,
    • DenseFuse, DRF, CSF
  • one GAN-based methods, i.e.,
    • FusionGAN
  • three CNN-based methods, i.e.,
    • IFCNN , PMG, U2Fusion
      图像融合论文baseline及其网络模型_第15张图片

SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer

笔记链接

  • GTF ,DenseFuseFusionGANIFCNNPMGISDNetU2Fusion
    图像融合论文baseline及其网络模型_第16张图片

2023

LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images

  • DenseFuseFusionGANIFCNN, CUNet, RFN-Nest, Res2Fusion, YDTR, SwinFusionU2Fusion
    图像融合论文baseline及其网络模型_第17张图片

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

笔记链接

  • DIDFuse, U2Fusion , SDNet, RFNet, TarDAL, DeFusionReCoNet.
    图像融合论文baseline及其网络模型_第18张图片

CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion

  • DenseFuse, FusionGAN, PMGIDIDFuse , GANMcC , RFN, MFEIF, U2Fusion, SwinFusion, SDNet, SMoA,arDAL

传送门

图像融合相关论文阅读笔记

[SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer]
[(MFEIF)Learning a Deep Multi-Scale Feature Ensemble and an Edge-Attention Guidance for Image Fusion]
[DenseFuse: A fusion approach to infrared and visible images]
[DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme Exposure Image Pair]
[GANMcC: A Generative Adversarial Network With Multiclassification Constraints for IVIF]
[DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion]
[IFCNN: A general image fusion framework based on convolutional neural network]
[(PMGI) Rethinking the image fusion: A fast unified image fusion network based on proportional maintenance of gradient and intensity]
[SDNet: A Versatile Squeeze-and-Decomposition Network for Real-Time Image Fusion]
[DDcGAN: A Dual-Discriminator Conditional Generative Adversarial Network for Multi-Resolution Image Fusion]
[FusionGAN: A generative adversarial network for infrared and visible image fusion]
[PIAFusion: A progressive infrared and visible image fusion network based on illumination aw]
[CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion]
[U2Fusion: A Unified Unsupervised Image Fusion Network]
综述[Visible and Infrared Image Fusion Using Deep Learning]

图像融合论文baseline总结

[图像融合论文baseline及其网络模型]

其他论文

[3D目标检测综述:Multi-Modal 3D Object Detection in Autonomous Driving:A Survey]

其他总结

[CVPR2023、ICCV2023论文题目汇总及词频统计]

✨精品文章总结

✨[图像融合论文及代码整理最全大合集]
✨[图像融合常用数据集整理]

如有疑问可联系:[email protected];
码字不易,【关注,收藏,点赞】一键三连是我持续更新的动力,祝各位早发paper,顺利毕业~

你可能感兴趣的:(图像融合,图像处理,人工智能,深度学习,论文阅读,论文笔记)