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Multimodal image fusion aims to integrate information from different imaging techniques to produce a comprehensive, detail-rich single image for downstream vision tasks.
In Proceedings 2003 International Conference on Image Processing
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IEEE Transactions on Image Processing
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IEEE Sensors Journal
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Information Fusion
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IEEE Signal Processing Letters
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Instrumentation and Measurement
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IEEE Transactions on Multimedia
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IEEE Transactions on Instrumentation and Measurement
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In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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IEEE Transactions on Image Processing
Ma, J., Xu, H., Jiang, J., Mei, X., and Zhang, X.: DDcGAN: A dual-discriminator conditional generative adversarial network for multi-resolution image fusion · 2020
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Computers in Biology and Medicine
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IEEE Transactions on Instrumentation and Measurement
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IEEE Transactions on Circuits and Systems for Video Technology
Tang, W., He, F., Liu, Y., Duan, Y., and Si, T.: DATFuse: Infrared and visible image fusion via dual attention transformer · 2023
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In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
Zhao, Z., Bai, H., Zhang, J., Zhang, Y., Xu, S., Lin, Z., et al.: CDDFuse: Correlation-driven dual-branch feature decomposition for multi-modality image fusion · 2023
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IEEE Transactions on Image Processing
Yu, Z., Zhou, B., Wan, J., Wang, P., Chen, H., and Liu, X., et al.: Searching multi-rate and multi-modal temporal enhanced networks for gesture recognition · 2021
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Information Fusion
Li, H., Wu, X., and Kittler, J.: RFN-Nest: An end-to-end residual fusion network for infrared and visible images · 2021
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In Proceedings of the IEEE/CVF International Conference on Computer Vision
Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., and Guo, B.: Swin transformer: Hierarchical vision transformer using shifted windows · 2021
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M. Ranzato, A. Beygelzimer, Y. N. Dauphin, et al. (Eds.), Proceedings of the 35th international conference on neural information processing systems
Gu, A., Johnson, I., Goel, K., Saab, K., Dao, T., Rudra, A., and Ré, C.: Combining recurrent, convolutional, and continuous-time models with linear state space layers · 2021
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International Journal of Computer Vision
Zhang, H and Ma, J.: SDNet: A versatile squeeze-and-decomposition network for real-time image fusion · 2021
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In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
Wang, J., Liu, A., Yin, Z., Liu, S., Tang, S., and Liu, X.: Dual attention suppression attack: Generate adversarial camouflage in physical world · 2021
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IEEE/CAA Journal of Automatica Sinica
Ma, J., Tang, L., Fan, F., Huang, J., Mei, X., and Ma, Y.: Swinfusion: Cross-domain long-range learning for general image fusion via swin transformer · 2022
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Gu, A., and Dao, T. Mamba: Linear-time sequence modeling with selective state spaces · 2023
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IEEE Transactions on Image Processing
Chang, Z., Feng, Z., Yang, S., and Gao, Q.: AFT: Adaptive fusion transformer for visible and infrared images · 2023
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Ye, Q., Yu, Z., Shao, R., Xie, X., Torr, P., and Cao, X.: CAT: Enhancing multimodal large language model to answer questions in dynamic audio-visual scenarios · 2024
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International Journal of Computer Vision
Yu, Z., Cai, R., Cui, Y., Liu, X., Hu, Y., and Kot, A.: Rethinking vision transformer and masked autoencoder in multimodal face anti-spoofing · 2024
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Information Fusion
Zhang, T., Tan, T., Han, L., Wang, X., Gao, Y., and Dijk, J., et al. IMPORTANT-Net: Integrated MRI multi-parametric increment fusion generator with attention network for synthesizing absent data · 2024
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arXiv preprint arXiv:2402.02491
Ruan, J and Xiang, S.: VM-Unet: Vision mamba unet for medical image segmentation · 2024
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arXiv preprint arXiv:2403.09977
Pei, X., Huang, T., and Xu, C.: EfficientVMamba: Atrous selective scan for light weight visual mamba · 2024
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International Journal of Computer Vision
Liu, J., Lin, R., Wu, G., Liu, R., Luo, Z., and Fan, X.: Coconet: Coupled contrastive learning network with multi-level feature ensemble for multi-modality image fusion · 2024
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IEEE Journal of Biomedical and Health Informatics
Xie, X., Zhang, X., Tang, X., Zhao, J., Xiong, D., and Ouyang, L., et al.: MACTFusion: Lightweight cross transformer for adaptive multimodal medical image fusion · 2024
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arXiv preprint arXiv:2401.10166
Liu, Y., Tian, Y., Zhao, Y. Yu, H., Xie, L., Wang, Y., Ye, Q., and Liu, Y.: VMamba: Visual state space model · 2024
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IEEE Transactions on Consumer Electronics
Ju, M., Xie, S., and Li, F.: Improving skip connection in u-net through fusion perspective with mamba for image dehazing · 2024
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arXiv preprint arXiv:2404.09146
Dong, W., Zhu, H., Lin, S., Luo, X., Shen, Y., and Liu, X., et al.: Fusion-mamba for cross-modality object detection · 2024
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arXiv preprint arXiv:2404.08406
Li, Z., Pan, H., Zhang, K., Wang, Y., and Yu, F.: Mambadfuse: A mamba-based dual-phase model for multi-modality image fusion · 2024
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In European Conference on Computer Vision
Guo, H., Li, J., Dai, T., Ouyang, Z., Ren, X., and Xia, S.: MambaIR: A simple baseline for image restoration with state-space model · 2025
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