mlsanityData to 7 Oct 2026

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

arXiv 2211.14461 ↗First posted 26 Nov 2022cs.CVcited by 222

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Cited by 22 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Multi-modality (MM) image fusion aims to render fused images that maintain the merits of different modalities, e.g., functional highlight and detailed textures. To tackle the challenge in modeling cross-modality features and decomposing desirable modality-specific and modality-shared features, we propose a novel Correlation-Driven feature Decomposition Fusion (CDDFuse) network. Firstly, CDDFuse uses Restormer blocks to extract cross-modality shallow features. We then introduce a dual-branch Transformer-CNN feature extractor with Lite Transformer (LT) blocks leveraging long-range attention to handle low-frequency global features and Invertible Neural Networks (INN) blocks focusing on extracting high-frequency local information. A correlation-driven loss is further proposed to make the low-frequency features correlated while the high-frequency features uncorrelated based on the embedded information. Then, the LT-based global fusion and INN-based local fusion layers output the fused image. Extensive experiments demonstrate that our CDDFuse achieves promising results in multiple fusion tasks, including infrared-visible image fusion and medical image fusion. We also show that CDDFuse can boost the performance in downstream infrared-visible semantic segmentation and object detection in a unified benchmark. The code is available at https://github.com/Zhaozixiang1228/MMIF-CDDFuse.

Key facts. Cited by 222 papers in the map (data through 7 Oct 2026). Builds on 51 of its 100 references that are in the map. First posted on arXiv 26 Nov 2022.

Builds on

51 of 100 references.

References · 51

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  4. 2020End-to-End Object Detection with Transformerscited by 7,384
  5. 2022Generative Adversarial Networkscited by 5,603
  6. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,773
  7. 2020Training data-efficient image transformers & distillation through attentioncited by 4,560
  8. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,410
  9. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  10. 2014Conditional Generative Adversarial Netscited by 2,152
  11. 2016Density estimation using Real NVPcited by 2,029
  12. 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutionscited by 1,960
38 more
  1. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,869
  2. 2020YOLOv4: Optimal Speed and Accuracy of Object Detectioncited by 1,624
  3. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  4. 2018Glow: Generative Flow with Invertible 1x1 Convolutionscited by 1,539
  5. 2020Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformerscited by 1,368
  6. 2014NICE: Non-linear Independent Components Estimationcited by 1,052
  7. 2016Least Squares Generative Adversarial Networkscited by 1,000
  8. 2020Pre-Trained Image Processing Transformercited by 891
  9. 2021Uformer: A General U-Shaped Transformer for Image Restorationcited by 864
  10. 2018Invertible Residual Networkscited by 364
  11. 2022Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detectioncited by 313
  12. 2018Analyzing Inverse Problems with Invertible Neural Networkscited by 239
  13. 2017The Reversible Residual Network: Backpropagation Without Storing Activationscited by 215
  14. 2018DenseFuse: A Fusion Approach to Infrared and Visible Imagescited by 180
  15. 2019Forward and Backward Information Retention for Accurate Binary Neural Networkscited by 169
  16. 2019Guided Image Generation with Conditional Invertible Neural Networkscited by 147
  17. 2018i-RevNet: Deep Invertible Networkscited by 137
  18. 2020Lite Transformer with Long-Short Range Attentioncited by 127
  19. 2021Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical Worldcited by 127
  20. 2021Video Super-Resolution Transformercited by 120
  21. 2021RFN-Nest: An end-to-end residual fusion network for infrared and visible imagescited by 109
  22. 2020Invertible Image Rescalingcited by 92
  23. 2021StrucTexT: Structured Text Understanding with Multi-Modal Transformerscited by 90
  24. 2022Unsupervised Misaligned Infrared and Visible Image Fusion via Cross-Modality Image Generation and Registrationcited by 80
  25. 2019Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusioncited by 78
  26. 2021RobustART: Benchmarking Robustness on Architecture Design and Training Techniquescited by 78
  27. 2020DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusioncited by 72
  28. 2021Discrete Cosine Transform Network for Guided Depth Map Super-Resolutioncited by 71
  29. 2022BiBERT: Accurate Fully Binarized BERTcited by 70
  30. 2020NestFuse: An Infrared and Visible Image Fusion Architecture based on Nest Connection and Spatial/Channel Attention Modelscited by 62
  31. 2019Training Robust Deep Neural Networks via Adversarial Noise Propagationcited by 60
  32. 2021Deep Gradient Projection Networks for Pan-sharpeningcited by 44
  33. 2022RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolutioncited by 44
  34. 2013Medical Image Fusion: A survey of the state of the artcited by 39
  35. 2022HyperTransformer: A Textural and Spectral Feature Fusion Transformer for Pansharpeningcited by 32
  36. 2021Distribution-sensitive Information Retention for Accurate Binary Neural Networkcited by 25
  37. 2020Bayesian Fusion for Infrared and Visible Imagescited by 14
  38. 2020Deep Convolutional Sparse Coding Networks for Image Fusioncited by 4

50 most cited of 51 All 51 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 24; 2024: 61; 2025: 79; 2026: 58.

222 papers.

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  1. 2023DDFM: Denoising Diffusion Model for Multi-Modality Image Fusioncited by 153
  2. 2023Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentationcited by 128
  3. 2023Equivariant Multi-Modality Image Fusioncited by 98
  4. 2024FusionMamba: Dynamic Feature Enhancement for Multimodal Image Fusion with Mambacited by 81
  5. 2023Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Modelcited by 69
  6. 2024Fusion-Mamba for Cross-modality Object Detectioncited by 67
  7. 2024Task-Customized Mixture of Adapters for General Image Fusioncited by 59
  8. 2023A Task-guided, Implicitly-searched and Meta-initialized Deep Model for Image Fusioncited by 47
  9. 2023Explicit Attention-Enhanced Fusion for RGB-Thermal Perception Taskscited by 41
  10. 2024Image Fusion via Vision-Language Modelcited by 40
  11. 2024CrossFuse: A Novel Cross Attention Mechanism based Infrared and Visible Image Fusion Approachcited by 38
  12. 2023An Interactively Reinforced Paradigm for Joint Infrared-Visible Image Fusion and Saliency Object Detectioncited by 36
38 more
  1. 2024MambaDFuse: A Mamba-based Dual-phase Model for Multi-modality Image Fusioncited by 35
  2. 2025Every SAM Drop Counts: Embracing Semantic Priors for Multi-Modality Image Fusion and Beyondcited by 34
  3. 2025DCEvo: Discriminative Cross-Dimensional Evolutionary Learning for Infrared and Visible Image Fusioncited by 34
  4. 2025One Model for ALL: Low-Level Task Interaction Is a Key to Task-Agnostic Image Fusioncited by 32
  5. 2024Text-DiFuse: An Interactive Multi-Modal Image Fusion Framework based on Text-modulated Diffusion Modelcited by 31
  6. 2023Spherical Space Feature Decomposition for Guided Depth Map Super-Resolutioncited by 28
  7. 2023Learning a Graph Neural Network with Cross Modality Interaction for Image Fusioncited by 28
  8. 2025ContextFlow: Training-Free Video Object Editing via Adaptive Context Enrichmentcited by 27
  9. 2023Bi-level Dynamic Learning for Jointly Multi-modality Image Fusion and Beyondcited by 26
  10. 2023PAIF: Perception-Aware Infrared-Visible Image Fusion for Attack-Tolerant Semantic Segmentationcited by 26
  11. 2023TextFusion: Unveiling the Power of Textual Semantics for Controllable Image Fusioncited by 26
  12. 2024Task-driven Image Fusion with Learnable Fusion Losscited by 24
  13. 2023BiBench: Benchmarking and Analyzing Network Binarizationcited by 22
  14. 2024E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detectioncited by 21
  15. 2023From Text to Pixels: A Context-Aware Semantic Synergy Solution for Infrared and Visible Image Fusioncited by 19
  16. 2023TFDet: Target-Aware Fusion for RGB-T Pedestrian Detectioncited by 18
  17. 2023Improving Misaligned Multi-modality Image Fusion with One-stage Progressive Dense Registrationcited by 17
  18. 2025Solving Inverse Problems with FLAIRcited by 16
  19. 2023ReFusion: Learning Image Fusion from Reconstruction with Learnable Loss via Meta-Learningcited by 15
  20. 2024MaeFuse: Transferring Omni Features with Pretrained Masked Autoencoders for Infrared and Visible Image Fusion via Guided Trainingcited by 15
  21. 2024DMFourLLIE: Dual-Stage and Multi-Branch Fourier Network for Low-Light Image Enhancementcited by 15
  22. 2025Neural Video Compression with Context Modulationcited by 15
  23. 2024All-weather Multi-Modality Image Fusion: Unified Framework and 100k Benchmarkcited by 14
  24. 2025WaveMamba: Wavelet-Driven Mamba Fusion for RGB-Infrared Object Detectioncited by 14
  25. 2025Efficient Rectified Flow for Image Fusioncited by 14
  26. 2024Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution using Conditional Diffusion Modelcited by 13
  27. 2024Conditional Controllable Image Fusioncited by 13
  28. 2024Decomposition-based Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentationcited by 12
  29. 2023FusionBooster: A Unified Image Fusion Boosting Paradigmcited by 11
  30. 2023Bridging the Gap between Multi-focus and Multi-modal: A Focused Integration Framework for Multi-modal Image Fusioncited by 11
  31. 2024Multi-modal Crowd Counting via a Broker Modalitycited by 11
  32. 2024TSJNet: A Multi-modality Target and Semantic Awareness Joint-driven Image Fusion Networkcited by 10
  33. 2024MMDRFuse: Distilled Mini-Model with Dynamic Refresh for Multi-Modality Image Fusioncited by 10
  34. 2024UMCFuse: A Unified Multiple Complex Scenes Infrared and Visible Image Fusion Frameworkcited by 9
  35. 2024Infrared and Visible Image Fusion with Language-Driven Loss in CLIP Embedding Spacecited by 9
  36. 2024Rethinking Early-Fusion Strategies for Improved Multispectral Object Detectioncited by 9
  37. 2024RoadFormer+: Delivering RGB-X Scene Parsing through Scale-Aware Information Decoupling and Advanced Heterogeneous Feature Fusioncited by 9
  38. 2025MMAIF: Multi-task and Multi-degradation All-in-One for Image Fusion with Language Guidancecited by 9

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