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MultMed(19), No. 7, July 2017, pp. 1454-1466.
IEEE DOI 1706
Clustering algorithms, Correlation, Data integration, Feature extraction, Learning systems, Optimization, Sparse matrices, Feature fusion, graph embedding, machine learning, multimodal data, sparse, representation BibRef

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Convolutional neural networks, (CNNs) BibRef

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Deep Multimodal Fusion: A Hybrid Approach,
IJCV(126), No. 2-4, April 2018, pp. 440-456.
Springer DOI 1804
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Multimodal fusion using dynamic hybrid models,
WACV14(556-563)
IEEE DOI 1406
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Applying stochastic second-order entropy images to multi-modal image registration,
SP:IC(65), 2018, pp. 201-209.
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Multi-modal image registration, Image-processing, Image matching, Entropy image, Structural representation, Second order entropy BibRef

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PRL(109), 2018, pp. 120-128.
Elsevier DOI 1806
Multiple data source mining, Pattern analysis, Data classification, Data clustering, Data fusion BibRef

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Shape-aware label fusion for multi-atlas frameworks,
PRL(124), 2019, pp. 109-117.
Elsevier DOI 1906
Multi-atlas label fusion, Shape models, Medical image segmentation BibRef

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Multiobject Fusion With Minimum Information Loss,
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IEEE DOI 2002
Generalized covariance intersection, Kullback-Leibler divergence, random finite set, data fusion, linear opinion pool BibRef

Yao, W.[Wei], Jiang, Y.[Ying], Lu, W.[Wenda], Chen, J.[Jun], Xie, L.C.[Lin-Chao],
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Boosting Structure Consistency for Multispectral and Multimodal Image Registration,
IP(29), 2020, pp. 5147-5162.
IEEE DOI 2004
Transforms, Image registration, Boosting, Correlation, Entropy, Image edge detection, Histograms, Multispectral image, optimization BibRef

Pamart, A.[Anthony], Morlet, F.[François], de Luca, L.[Livio], Veron, P.[Philippe],
A Robust and Versatile Pipeline for Automatic Photogrammetric-Based Registration of Multimodal Cultural Heritage Documentation,
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Meher, B.[Bikash], Agrawal, S.[Sanjay], Panda, R.[Rutuparna], Dora, L.[Lingraj], Abraham, A.[Ajith],
A novel region-based multimodal image fusion technique using improved dictionary learning,
IJIST(30), No. 3, 2020, pp. 558-576.
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Image understanding via learning weakly-supervised cross-modal semantic translation,
JVCIR(71), 2020, pp. 102789.
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Image understanding, Cross-modal semantic translation, Weakly-supervised learning BibRef

Wang, S.Y.[Shi-Ying], Shen, Y.[Yan],
Multi-modal image fusion based on saliency guided in NSCT domain,
IET-IPR(14), No. 13, November 2020, pp. 3188-3201.
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Multimodal image fusion based on point-wise mutual information,
IVC(105), 2021, pp. 104047.
Elsevier DOI 2101
Image fusion, Multimodal, Point-wise mutual information, Markov random field model, Gradient domain BibRef

Kavipriya, A., Muthukumar, A.,
Special Issue Retraction: Innovative approach for multimodal fusion recognition based feature extraction using band-limited phase-only correlation and discrete orthonormal Stockwell transform,
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DOI Link 2103
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Robust Dynamic Multi-Modal Data Fusion: A Model Uncertainty Perspective,
SPLetters(28), 2021, pp. 2107-2111.
IEEE DOI 2112
Data models, Heuristic algorithms, Signal processing algorithms, Uncertainty, Computational modeling, Bayes methods, Task analysis, particle filter BibRef

Liu, R.S.[Ri-Sheng], Liu, J.Y.[Jin-Yuan], Jiang, Z.Y.[Zhi-Ying], Fan, X.[Xin], Luo, Z.X.[Zhong-Xuan],
A Bilevel Integrated Model With Data-Driven Layer Ensemble for Multi-Modality Image Fusion,
IP(30), 2021, pp. 1261-1274.
IEEE DOI 2012
Image fusion, Task analysis, Transforms, Optimization, Magnetic resonance imaging, Dictionaries, neural networks BibRef

Liu, J.Y.[Jin-Yuan], Lin, R.J.[Run-Jia], Wu, G.Y.[Guan-Yao], Liu, R.S.[Ri-Sheng], Luo, Z.X.[Zhong-Xuan], Fan, X.[Xin],
CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion,
IJCV(132), No. 5, May 2024, pp. 1748-1775.
Springer DOI 2405
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Xu, H.[Han], Ma, J.Y.[Jia-Yi], Jiang, J.J.[Jun-Jun], Guo, X.J.[Xiao-Jie], Ling, H.B.[Hai-Bin],
U2Fusion: A Unified Unsupervised Image Fusion Network,
PAMI(44), No. 1, January 2022, pp. 502-518.
IEEE DOI 2112
Image fusion, Task analysis, Feature extraction, Measurement, Supervised learning, Data mining, Training, Image fusion, continual learning BibRef

Mao, Y.D.[Yu-Dong], Jiang, Q.P.[Qiu-Ping], Cong, R.M.[Run-Min], Gao, W.[Wei], Shao, F.[Feng], Kwong, S.[Sam],
Cross-Modality Fusion and Progressive Integration Network for Saliency Prediction on Stereoscopic 3D Images,
MultMed(24), 2022, pp. 2435-2448.
IEEE DOI 2205
Feature extraction, Fuses, Decoding, Predictive models, Pipelines, Visualization, Stereoscopic 3D image, Progressive integration BibRef

Wang, J.P.[Jin-Ping], Li, J.[Jun], Shi, Y.L.[Yan-Li], Lai, J.H.[Jian-Huang], Tan, X.J.[Xiao-Jun],
AM³Net: Adaptive Mutual-Learning-Based Multimodal Data Fusion Network,
CirSysVideo(32), No. 8, August 2022, pp. 5411-5426.
IEEE DOI 2208
Feature extraction, Laser radar, Convolution, Kernel, Data integration, Convolutional neural networks, and multimodal data classification BibRef

Tu, H.W.[Huang-Wei], Zhu, Y.[Yu], Han, C.P.[Chang-Pei],
RI-LPOH: Rotation-Invariant Local Phase Orientation Histogram for Multi-Modal Image Matching,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
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Öfverstedt, J.[Johan], Lindblad, J.[Joakim], Sladoje, N.[Nataša],
Fast computation of mutual information in the frequency domain with applications to global multimodal image alignment,
PRL(159), 2022, pp. 196-203.
Elsevier DOI 2206
Mutual information, Image alignment, Global optimization, Multimodal, Entropy BibRef

Marivani, I.[Iman], Tsiligianni, E.[Evaggelia], Cornelis, B.[Bruno], Deligiannis, N.[Nikos],
Designing CNNs for Multimodal Image Restoration and Fusion via Unfolding the Method of Multipliers,
CirSysVideo(32), No. 9, September 2022, pp. 5830-5845.
IEEE DOI 2209
Image restoration, Image fusion, Computational modeling, Convolutional neural networks, Task analysis, Image resolution, multimodal CNN BibRef

Wang, J.[Jing], Zhang, W.J.[Wen-Juan], Zhu, R.[Rui],
A multimodal molecular image fusion method based on relative total variation and co-saliency detection,
IJIST(33), No. 2, 2023, pp. 523-546.
DOI Link 2303
image fusion, molecular image, multimodality, relative total variation, saliency detection BibRef

Xu, H.[Han], Yuan, J.[Jiteng], Ma, J.Y.[Jia-Yi],
MURF: Mutually Reinforcing Multi-Modal Image Registration and Fusion,
PAMI(45), No. 10, October 2023, pp. 12148-12166.
IEEE DOI 2310
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Xu, H.[Han], Ma, J.Y.[Jia-Yi], Yuan, J.[Jiteng], Le, Z.L.[Zhu-Liang], Liu, W.[Wei],
RFNet: Unsupervised Network for Mutually Reinforcing Multi-modal Image Registration and Fusion,
CVPR22(19647-19656)
IEEE DOI 2210
Measurement, Deformable models, Image registration, Pattern recognition, Task analysis, Image fusion, Low-level vision BibRef

Li, J.Y.[Jia-Yuan], Hu, Q.W.[Qing-Wu], Zhang, Y.J.[Yong-Jun],
Multimodal Image Matching: A Scale-Invariant Algorithm and an Open Dataset,
PandRS(204), 2023, pp. 77-88.
Elsevier DOI 2310
Image matching, Feature descriptor, Dataset, SAR-optical, Multimodal images BibRef

Zhou, Y.[Yang], Han, Z.[Zhen], Dou, Z.[Zeng], Huang, C.B.[Cheng-Bin], Cong, L.[Li], Lv, N.[Ning], Chen, C.[Chen],
Edge Consistency Feature Extraction Method for Multi-Source Image Registration,
RS(15), No. 20, 2023, pp. 5051.
DOI Link 2310
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Lu, H.J.[Heng-Jie], Xu, S.G.[Shu-Gong], Wang, J.H.[Jia-Hao],
Multi-dataset fusion for multi-task learning on face attribute recognition,
PRL(173), 2023, pp. 72-78.
Elsevier DOI 2310
Face attribute recognition, Multi-dataset fusion, Multi-task learning, Knowledge distillation, Deep learning BibRef

Wei, J.[Jiwei], Yang, Y.[Yang], Xu, X.[Xing], Song, J.K.[Jing-Kuan], Wang, G.Q.[Guo-Qing], Shen, H.T.[Heng Tao],
Less is Better: Exponential Loss for Cross-Modal Matching,
CirSysVideo(33), No. 9, September 2023, pp. 5271-5280.
IEEE DOI 2310
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Islam, M.M.[Md Mofijul], Yasar, M.S.[Mohammad Samin], Iqbal, T.[Tariq],
MAVEN: A Memory Augmented Recurrent Approach for Multimodal Fusion,
MultMed(25), 2023, pp. 3694-3708.
IEEE DOI 2310
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Wang, Q.[Qun], Yang, B.[Boli], Li, L.[Luchun], Liang, H.Y.[Hong-Yi], Zhu, X.L.[Xiao-Lin], Cao, R.[Ruyin],
Within-Season Crop Identification by the Fusion of Spectral Time-Series Data and Historical Crop Planting Data,
RS(15), No. 20, 2023, pp. 5043.
DOI Link 2310
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Zhang, J.[Jun], Jiao, L.C.[Li-Cheng], Ma, W.P.[Wen-Ping], Liu, F.[Fang], Liu, X.[Xu], Li, L.L.[Ling-Ling], Chen, P.[Puhua], Yang, S.Y.[Shu-Yuan],
Transformer Based Conditional GAN for Multimodal Image Fusion,
MultMed(25), 2023, pp. 8988-9001.
IEEE DOI 2312
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Wang, J.P.[Jin-Ping], Tan, X.J.[Xiao-Jun],
Mutually Beneficial Transformer for Multimodal Data Fusion,
CirSysVideo(33), No. 12, December 2023, pp. 7466-7479.
IEEE DOI 2312
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Luo, X.[Xing], Fu, G.Z.[Gui-Zhong], Yang, J.X.[Jiang-Xin], Cao, Y.L.[Yan-Long], Cao, Y.P.[Yan-Peng],
Multi-Modal Image Fusion via Deep Laplacian Pyramid Hybrid Network,
CirSysVideo(33), No. 12, December 2023, pp. 7354-7369.
IEEE DOI Code:
WWW Link. 2312
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Yan, X.[Xiaohu], Cao, Y.H.[Yi-Hang], Yang, Y.J.[Yi-Jun], Yao, Y.X.[Yong-Xiang],
Multi-Modal Image Registration Based on Phase Exponent Differences of the Gaussian Pyramid,
RS(15), No. 24, 2023, pp. 5764.
DOI Link 2401
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Chen, R.[Rui], Zhao, L.[Long],
Two-Level Integrity-Monitoring Method for Multi-Source Information Fusion Navigation,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
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Li, J.Y.[Jia-Yao], Li, L.[Li], Sun, R.Z.[Rui-Zhi], Yuan, G.[Gang], Wang, S.[Shufan], Sun, S.[Shulin],
MMAN-M2: Multiple multi-head attentions network based on encoder with missing modalities,
PRL(177), 2024, pp. 110-120.
Elsevier DOI 2401
Multi-modal fusion, Multi-head attention, Random missing modalities, Encoder-decoder, Missing modalities BibRef

Zhao, Z.X.[Zi-Xiang], Bai, H.W.[Hao-Wen], Zhu, Y.Z.[Yuan-Zhi], Zhang, J.S.[Jiang-She], Xu, S.[Shuang], Zhang, Y.[Yulun], Zhang, K.[Kai], Meng, D.Y.[De-Yu], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
DDFM: Denoising Diffusion Model for Multi-Modality Image Fusion,
ICCV23(8048-8059)
IEEE DOI Code:
WWW Link. 2401
BibRef

Sun, Y.[Yuli], Lei, L.[Lin], Li, Z.[Zhang], Kuang, G.Y.[Gang-Yao],
Similarity and dissimilarity relationships based graphs for multimodal change detection,
PandRS(208), 2024, pp. 70-88.
Elsevier DOI Code:
WWW Link. 2402
Multimodal change detection, Dissimilarity relationship, k-farthest neighbors, k-nearest neighbors, Image regression BibRef

Zhao, Y.Y.[Yang-Yang], Zheng, Q.C.[Qing-Chun], Zhu, P.H.[Pei-Hao], Zhang, X.[Xu], Ma, W.P.[Wen-Peng],
TUFusion: A Transformer-Based Universal Fusion Algorithm for Multimodal Images,
CirSysVideo(34), No. 3, March 2024, pp. 1712-1725.
IEEE DOI Code:
WWW Link. 2403
Image fusion, Transformers, Feature extraction, Biomedical imaging, Deep learning, Heuristic algorithms, Visualization, fusion strategy BibRef

Moreshet, A.[Aviad], Keller, Y.[Yosi],
Attention-based multimodal image matching,
CVIU(241), 2024, pp. 103949.
Elsevier DOI 2403
Multisensor image matching, Deep learning, Attention-based BibRef

Liu, J.Y.[Jin-Yang], Li, S.T.[Shu-Tao], Dian, R.[Renwei], Song, Z.[Ze],
Focus Relationship Perception for Unsupervised Multi-Focus Image Fusion,
MultMed(26), 2024, pp. 6155-6165.
IEEE DOI 2404
Image fusion, Feature extraction, Loss measurement, Data mining, Visual perception, Tensors, Optimization, Multi-focus image fusion, unsupervised learning BibRef

He, X.W.[Xin-Wei], Cheng, S.[Silin], Liang, D.K.[Ding-Kang], Bai, S.[Song], Wang, X.[Xi], Zhu, Y.Y.[Ying-Ying],
LATFormer: Locality-Aware Point-View Fusion Transformer for 3D shape recognition,
PR(151), 2024, pp. 110413.
Elsevier DOI 2404
3D shape retrieval and classification, Point cloud, Multi-view, Multimodal fusion, Transformer BibRef

Almarines, N.R.[Nico R.], Hashimoto, S.[Shizuka], Pulhin, J.M.[Juan M.], Tiburan, C.L.[Cristino L.], Magpantay, A.T.[Angelica T.], Saito, O.[Osamu],
Influence of Image Compositing and Multisource Data Fusion on Multitemporal Land Cover Mapping of Two Philippine Watersheds,
RS(16), No. 12, 2024, pp. 2167.
DOI Link 2406
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Sun, L.[Le], Tang, M.Q.[Meng-Qi], Muhammad, G.[Ghulam],
CABnet: A channel attention dual adversarial balancing network for multimodal image fusion,
IVC(147), 2024, pp. 105065.
Elsevier DOI 2406
Image processing, Infrared and visible image fusion, Complementary information extract, Adaptive factor BibRef

Deng, X.[Xin], Liu, E.[Enpeng], Gao, C.[Chao], Li, S.X.[Sheng-Xi], Gu, S.H.[Shu-Hang], Xu, M.[Mai],
CrossHomo: Cross-Modality and Cross-Resolution Homography Estimation,
PAMI(46), No. 8, August 2024, pp. 5725-5742.
IEEE DOI 2407
Estimation, Image resolution, Feature extraction, Superresolution, Deep learning, Task analysis, Spatial resolution, multi-modal image registration BibRef

Lin, S.Y.[Shu-Yuan], Huang, F.R.[Fei-Ran], Lai, T.T.[Tao-Tao], Lai, J.H.[Jian-Huang], Wang, H.Z.[Han-Zi], Weng, J.[Jian],
Robust Heterogeneous Model Fitting for Multi-source Image Correspondences,
IJCV(132), No. 8, August 2024, pp. 2907-2928.
Springer DOI 2408
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Li, C.[Can], Zuo, Z.[Zhen], Tong, X.Z.[Xiao-Zhong], Huang, H.[Honghe], Yuan, S.D.[Shu-Dong], Dang, Z.Y.[Zhao-Yang],
CPROS: A Multimodal Decision-Level Fusion Detection Method Based on Category Probability Sets,
RS(16), No. 15, 2024, pp. 2745.
DOI Link 2408
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Deng, Y.[Yaohua], Liu, X.[Xiali], Yang, K.[Kenan], Li, Z.H.[Ze-Hang],
Flexible thin parts multi-target positioning method of multi-level feature fusion,
IET-IPR(18), No. 11, 2024, pp. 2996-3012.
DOI Link 2409
Gaussian processes, image fusion, image recognition, object recognition BibRef

Tang, Y.Q.[Yu-Qi], Yang, X.[Xin], Han, T.[Te], Sun, K.[Kai], Guo, Y.Q.[Yu-Qiang], Hu, J.[Jun],
Iterative Optimization-Enhanced Contrastive Learning for Multimodal Change Detection,
RS(16), No. 19, 2024, pp. 3624.
DOI Link 2410
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Han, W.C.[Wen-Cheng], Dong, X.P.[Xing-Ping], Zhang, Y.Y.[Yi-Yuan], Crandall, D.[David], Xu, C.Z.[Cheng-Zhong], Shen, J.B.[Jian-Bing],
Asymmetric Convolution: An Efficient and Generalized Method to Fuse Feature Maps in Multiple Vision Tasks,
PAMI(46), No. 11, November 2024, pp. 7363-7376.
IEEE DOI 2410
Task analysis, Fuses, Feature extraction, Visualization, Convolution, Target tracking, Shape, Asymmetric convolution, feature maps, vision tasks BibRef

Wu, Q.[Quan], Yu, Q.[Qida],
A Fast Sequential Similarity Detection Algorithm for Multi-Source Image Matching,
RS(16), No. 19, 2024, pp. 3589.
DOI Link 2410
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Saidi, S.[Souad], Idbraim, S.[Soufiane], Karmoude, Y.[Younes], Masse, A.[Antoine], Arbelo, M.[Manuel],
Deep-Learning for Change Detection Using Multi-Modal Fusion of Remote Sensing Images: A Review,
RS(16), No. 20, 2024, pp. 3852.
DOI Link 2411
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Liu, Y.Y.[Yu-Yan], He, W.[Wei], Zhang, H.Y.[Hong-Yan],
GRiD: Guided Refinement for Detector-Free Multimodal Image Matching,
IP(33), 2024, pp. 5892-5906.
IEEE DOI 2411
Feature extraction, Image matching, Transformers, Optical imaging, Detectors, Semantics, Image edge detection, Adaptive optics, multimodal images BibRef

Wang, J.P.[Jin-Peng], Su, N.[Nan], Zhao, C.H.[Chun-Hui], Yan, Y.M.[Yi-Ming], Feng, S.[Shou],
Multi-Modal Object Detection Method Based on Dual-Branch Asymmetric Attention Backbone and Feature Fusion Pyramid Network,
RS(16), No. 20, 2024, pp. 3904.
DOI Link 2411
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Liu, Y.[Yang], Liu, F.[Fang], Jiao, L.C.[Li-Cheng], Bao, Q.Y.[Qian-Yue], Sun, L.[Long], Li, S.[Shuo], Li, L.L.[Ling-Ling], Liu, X.[Xu],
Multi-Grained Gradual Inference Model for Multimedia Event Extraction,
CirSysVideo(34), No. 10, October 2024, pp. 10507-10520.
IEEE DOI 2411
Visualization, Data mining, Task analysis, Streaming media, Feature extraction, Boats, multimodal alignment BibRef

Wang, X.X.[Xiang-Xiang], Fang, L.X.[Li-Xing], Zhao, J.L.[Jun-Li], Pan, Z.K.[Zhen-Kuan], Li, H.[Hui], Li, Y.[Yi],
MMAE: A universal image fusion method via mask attention mechanism,
PR(158), 2025, pp. 111041.
Elsevier DOI Code:
WWW Link. 2411
Deep learning, Image fusion, Universal, Mask attention mechanism BibRef

Zhang, D.[Duoyi], Bashar, M.A.[Md Abul], Nayak, R.[Richi],
A novel multi-modal fusion method based on uncertainty-guided meta-learning,
PR(158), 2025, pp. 110993.
Elsevier DOI 2411
Multi-modal fusion, Neural networks, Feature-level bias, Uncertainty estimation, Meta-learning framework BibRef

Lv, T.[Ting], Ji, C.M.[Chuan-Ming], Jiang, H.[Hong], Liu, Y.[Yu],
HF2TNet: A Hierarchical Fusion Two-Stage Training Network for Infrared and Visible Image Fusion,
SPLetters(31), 2024, pp. 3164-3168.
IEEE DOI 2411
Feature extraction, Training, Image reconstruction, Image fusion, Transformers, Decoding, Convolution, Vectors BibRef

Meng, X.C.[Xiang-Chao], Chen, C.Q.[Chao-Qi], Liu, Q.[Qiang], Shao, F.[Feng],
Multi-domain pseudo-reference quality evaluation for infrared and visible image fusion,
IET-IPR(18), No. 13, 2024, pp. 4095-4113.
DOI Link 2411
image enhancement, image fusion BibRef

Bai, Y.[Yang], Gao, M.[Meijing], Li, S.Y.[Shi-Yu], Wang, P.[Ping], Guan, N.[Ning], Yin, H.Z.[Hao-Zheng], Yan, Y.H.[Yong-Hao],
IBFusion: An Infrared and Visible Image Fusion Method Based on Infrared Target Mask and Bimodal Feature Extraction Strategy,
MultMed(26), 2024, pp. 10610-10622.
IEEE DOI 2411
Feature extraction, Image fusion, Data mining, Deep learning, Training, Generative adversarial networks, Degradation, bimodal feature extraction BibRef

Wang, X.X.[Xiang-Xiang], Fang, L.X.[Li-Xing], Zhao, J.L.[Jun-Li], Pan, Z.K.[Zhen-Kuan], Li, H.[Hui], Li, Y.[Yi],
UUD-Fusion: An unsupervised universal image fusion approach via generative diffusion model,
CVIU(249), 2024, pp. 104218.
Elsevier DOI Code:
WWW Link. 2412
Two-stage unsupervised universal image fusion. Unsupervised, Universal, Image fusion, Diffusion, Sampling algorithm BibRef

Dong, A.[Aimei], Wang, L.[Long], Liu, J.[Jian], Xu, J.Y.[Jing-Yuan], Zhao, G.X.[Gui-Xin], Zhai, Y.[Yi], Lv, G.H.[Guo-Hua], Cheng, J.[Jinyong],
Co-Enhancement of Multi-Modality Image Fusion and Object Detection via Feature Adaptation,
CirSysVideo(34), No. 12, December 2024, pp. 12624-12637.
IEEE DOI 2501
Image fusion, Task analysis, Semantics, Feature extraction, Object detection, Visualization, Visual perception, Image fusion, mutual promotion BibRef

Wu, X.[Xiao], Cao, Z.H.[Zi-Han], Huang, T.Z.[Ting-Zhu], Deng, L.J.[Liang-Jian], Chanussot, J.[Jocelyn], Vivone, G.[Gemine],
Fully-Connected Transformer for Multi-Source Image Fusion,
PAMI(47), No. 3, March 2025, pp. 2071-2088.
IEEE DOI 2502
Algebra, Imaging, Pansharpening, Image representation, Transformers, Mathematical models, Computational efficiency, Sensors, visible and infrared image fusion BibRef

Hussain, I.[Israr], Tan, S.Q.[Shun-Quan], Huang, J.W.[Ji-Wu],
Few-Shot Based Learning Recaptured Image Detection with Multi-Scale Feature Fusion and Attention,
PR(161), 2025, pp. 111248.
Elsevier DOI 2502
Recaptured image detection, Few-shot learning, Multi-scale attention, Attention mechanism, Efficient-Net-models BibRef

Tang, H.[Hao], Liu, D.W.[Da-Wei], Shen, C.C.[Cheng-Chao],
Data-efficient multi-scale fusion vision transformer,
PR(161), 2025, pp. 111305.
Elsevier DOI Code:
WWW Link. 2502
Deep learning, Image classification, Vision transformer, Data efficiency, Multi-scale fusion BibRef

Liu, T.F.[Tong-Fei], Zhang, M.Y.[Ming-Yang], Gong, M.[Maoguo], Zhang, Q.F.[Qing-Fu], Jiang, F.L.[Fen-Long], Zheng, H.H.[Han-Hong], Lu, D.[Di],
Commonality Feature Representation Learning for Unsupervised Multimodal Change Detection,
IP(34), 2025, pp. 1219-1233.
IEEE DOI 2502
Feature extraction, Image reconstruction, Training, Data mining, Autoencoders, Representation learning, Image sensors, Decoding, commonality feature BibRef

Liu, Z.W.[Zhan-Wen], Cheng, J.[Juanru], Fan, J.[Jin], Lin, S.[Shan], Wang, Y.[Yang], Zhao, X.M.[Xiang-Mo],
Multi-Modal Fusion Based on Depth Adaptive Mechanism for 3D Object Detection,
MultMed(27), 2025, pp. 707-717.
IEEE DOI 2502
Point cloud compression, Feature extraction, Object detection, Laser radar, Image color analysis, Detectors, Deep learning, camera sensor BibRef

Dong, C.[Chunru], Wang, L.Z.[Li-Zhen], Zhang, F.[Feng], Hua, Q.[Qiang],
Multi-modal Few-shot Image Recognition with enhanced semantic and visual integration,
IVC(157), 2025, pp. 105490.
Elsevier DOI 2504
Few-shot image recognition, Multi-modal fusion, Similarity measurement BibRef

Tang, L.[Long], Liu, Y.[Yelei], Tian, Y.J.[Ying-Jie], Pardalos, P.M.[Panos M],
Complementary label learning with multi-view data and a semi-supervised labeling mechanism,
PR(165), 2025, pp. 111651.
Elsevier DOI 2505
Complementary label learning, Semi-supervised labeling, Multi-view fusion, Consensus principle, Complementary principle BibRef

Zhou, M.[Man], Huang, J.[Jie], Yan, K.Y.[Ke-Yu], Hong, D.F.[Dan-Feng], Jia, X.P.[Xiu-Ping], Chanussot, J.[Jocelyn], Li, C.Y.[Chong-Yi],
A General Spatial-Frequency Learning Framework for Multimodal Image Fusion,
PAMI(47), No. 7, July 2025, pp. 5281-5298.
IEEE DOI 2506
Frequency-domain analysis, Superresolution, Image fusion, Task analysis, Spatial resolution, Remote sensing, Convolution, multimodal image fusion BibRef

Wang, Z.[Zeyu], Zhao, L.[Libo], Zhang, J.Z.[Ji-Zheng], Song, R.[Rui], Song, H.Y.[Hai-Yu], Meng, J.[Jiana], Wang, S.D.[Shi-Dong],
Multi-Text Guidance Is Important: Multi-Modality Image Fusion via Large Generative Vision-Language Model,
IJCV(133), No. 7, July 2025, pp. 4646-4668.
Springer DOI 2506
BibRef

Liu, Y.[Yi], Li, C.X.[Cheng-Xin], Xu, S.K.[Shou-Kun], Han, J.G.[Jun-Gong],
Part-Whole Relational Fusion Towards Multi-Modal Scene Understanding,
IJCV(133), No. 7, July 2025, pp. 4483-4503.
Springer DOI Code:
WWW Link. 2506
BibRef

Ravi, J.[Jampani], Narmadha, R.,
A Systematic Literature Review on Multimodal Image Fusion Models with Challenges and Future Research Trends,
IJIG(25), No. 4, July 2025, pp. 2550039.
DOI Link 2507
BibRef

Liu, Y.P.[Ye-Peng], Sun, Z.C.[Zhi-Chao], Yu, B.S.[Bao-Sheng], Zhao, Y.T.[Yi-Tian], Du, B.[Bo], Xu, Y.C.[Yong-Chao], Cheng, J.[Jun],
MIFNet: Learning Modality-Invariant Features for Generalizable Multimodal Image Matching,
IP(34), 2025, pp. 3593-3608.
IEEE DOI Code:
WWW Link. 2507
Image matching, Feature extraction, Training, Graph neural networks, Diffusion models, Detectors, Semantics, feature descriptor optimization BibRef

Yang, Z.[Zeyu], Song, N.[Nan], Li, W.[Wei], Zhu, X.T.[Xia-Tian], Zhang, L.[Li], Torr, P.H.S.[Philip H.S.],
DeepInteraction++: Multi-Modality Interaction for Autonomous Driving,
PAMI(47), No. 8, August 2025, pp. 6749-6763.
IEEE DOI 2507
Point cloud compression, Object detection, Feature extraction, Laser radar, Autonomous vehicles, Decoding, Cameras, Transformers, multi-modal fusion BibRef

Mei, S.B.[Shi-Bin], Ni, B.B.[Bing-Bing], Wang, H.[Hang], Zhao, C.L.[Cheng-Long], Hu, F.[Fengfa], Pi, Z.M.[Zhi-Ming], Ke, B.[Bilian],
Object-Oriented Anchoring and Modal Alignment in Multimodal Learning,
ECCV24(L: 179-196).
Springer DOI 2412
BibRef

Tran, Q.H.[Quoc-Huy], Ahmed, M.[Muhammad], Popattia, M.[Murad], Ahmed, M.H.[M. Hassan], Konin, A.[Andrey], Zia, M.Z.[M. Zeeshan],
Learning by Aligning 2D Skeleton Sequences and Multi-Modality Fusion,
ECCV24(L: 141-161).
Springer DOI 2412
BibRef

Li, C.X.[Chen-Xin], Liu, X.Y.[Xin-Yu], Wang, C.[Cheng], Liu, Y.F.[Yi-Fan], Yu, W.H.[Wei-Hao], Shao, J.[Jing], Yuan, Y.X.[Yi-Xuan],
GTP-4O: Modality-prompted Heterogeneous Graph Learning for Omni-modal Biomedical Representation,
ECCV24(IV: 168-187).
Springer DOI 2412
BibRef

Song, Z.Q.[Ze-Qun], Wang, L.F.[Ling-Feng],
Dual Multi-Modal Feature Fusion Network for the Evaluation of Osteosarcoma,
ICIP24(2937-2943)
IEEE DOI 2411
Accuracy, Feature extraction, Data augmentation, Tumors, Biomedical imaging, Dual input, Multi-modal information, Osteosarcoma evaluation BibRef

Bahaduri, B.[Bissmella], Ming, Z.H.[Zu-Heng], Feng, F.C.[Fang-Chen], Mokraoui, A.[Anissa],
Multimodal Transformer Using Cross-Channel Attention for Object Detection in Remote Sensing Images,
ICIP24(2620-2626)
IEEE DOI 2411
Convolutional codes, Object detection, Self-supervised learning, Transformers, Robustness, Sensors, Multimodal fusion, remote sensing imagery BibRef

Gao, Z.X.[Zi-Xian], Jiang, X.[Xun], Xu, X.[Xing], Shen, F.M.[Fu-Min], Li, Y.J.[Yu-Jie], Shen, H.T.[Heng Tao],
Embracing Unimodal Aleatoric Uncertainty for Robust Multimodal Fusion,
CVPR24(26866-26875)
IEEE DOI 2410
Uncertainty, Noise, Contrastive learning, Benchmark testing, Robustness, Multimodal Fusion, Information Bottleneck BibRef

Jiang, H.[Hanwen], Karpur, A.[Arjun], Cao, B.[Bingyi], Huang, Q.X.[Qi-Xing], Araujo, A.[Andre],
OmniGlue: Generalizable Feature Matching with Foundation Model Guidance,
CVPR24(19865-19875)
IEEE DOI Code:
WWW Link. 2410
Training, Codes, Attention mechanisms, Computational modeling, Image matching, Benchmark testing BibRef

Yi, X.P.[Xun-Peng], Xu, H.[Han], Zhang, H.[Hao], Tang, L.F.[Lin-Feng], Ma, J.Y.[Jia-Yi],
Text-IF: Leveraging Semantic Text Guidance for Degradation-Aware and Interactive Image Fusion,
CVPR24(27016-27025)
IEEE DOI Code:
WWW Link. 2410
Degradation, Codes, Semantics, Pipelines, Feature extraction, Image fusion, Multi-modal fusion, Text BibRef

Vouitsis, N.[Noël], Liu, Z.Y.[Zhao-Yan], Gorti, S.K.[Satya Krishna], Villecroze, V.[Valentin], Cresswell, J.C.[Jesse C.], Yu, G.[Guangwei], Loaiza-Ganem, G.[Gabriel], Volkovs, M.[Maksims],
Data-Efficient Multimodal Fusion on a Single GPU,
CVPR24(27229-27241)
IEEE DOI Code:
WWW Link. 2410
Costs, Codes, Art, Computational modeling, Text to image, Graphics processing units, multimodal, efficient, CLIP, mixup BibRef

Zhao, Z.X.[Zi-Xiang], Bai, H.W.[Hao-Wen], Zhang, J.S.[Jiang-She], Zhang, Y.[Yulun], Zhang, K.[Kai], Xu, S.[Shuang], Chen, D.D.[Dong-Dong], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Equivariant Multi-Modality Image Fusion,
CVPR24(25912-25921)
IEEE DOI Code:
WWW Link. 2410
Training, Image sensors, Image segmentation, Self-supervised learning, low-level vision BibRef

Li, X.[Xilai], Li, X.S.[Xiao-Song], Ye, T.[Tao], Cheng, X.Q.[Xiao-Qi], Liu, W.Y.[Wu-Yang], Tan, H.[Haishu],
Bridging the Gap between Multi-focus and Multi-modal: A Focused Integration Framework for Multi-modal Image Fusion,
WACV24(1617-1626)
IEEE DOI Code:
WWW Link. 2404
Optical filters, Smoothing methods, Fuses, Estimation, Object detection, Optical imaging, Maintenance, Algorithms, Autonomous Driving BibRef

Han, K.Y.[Kai-Yang], Cao, F.[Fanzhi], Shi, T.X.[Tian-Xin], Wang, P.[Pu],
A Dual Attention Network for Multimodal Remote Sensing Image Matching,
CVIDL23(128-134)
IEEE DOI 2403
Training, Deep learning, Image matching, Nonlinear distortion, Imaging, Sensors, multimodal image matching, attention mechanism BibRef

Liu, B.[Bing], Xu, Z.Q.[Zi-Qi], Bao, X.L.[Xue-Liang], Zhong, Z.[Zhaohao],
MUNformer: A strong encoder that uses multi-level features extracted by different feature extractors for fusion,
CVIDL23(291-295)
IEEE DOI 2403
Semantics, Feature extraction, Transformers, Decoding, Data mining, component, semantic segmentation BibRef

He, C.M.[Chun-Ming], Li, K.[Kai], Xu, G.X.[Guo-Xia], Zhang, Y.[Yulun], Hu, R.[Runze], Guo, Z.H.[Zhen-Hua], Li, X.[Xiu],
Degradation-Resistant Unfolding Network for Heterogeneous Image Fusion,
ICCV23(12577-12587)
IEEE DOI 2401
BibRef

Liu, J.Y.[Jin-Yuan], Liu, Z.[Zhu], Wu, G.Y.[Guan-Yao], Ma, L.[Long], Liu, R.S.[Ri-Sheng], Zhong, W.[Wei], Luo, Z.X.[Zhong-Xuan], Fan, X.[Xin],
Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation,
ICCV23(8081-8090)
IEEE DOI Code:
WWW Link. 2401
BibRef

Sippel, F.[Frank], Seiler, J.[Jürgen], Kaup, A.[André],
Cross Spectral Image Reconstruction Using a Deep Guided Neural Network,
ICIP23(226-230)
IEEE DOI 2312
BibRef

Myers, A.[Audun], Kvinge, H.[Henry], Emerson, T.[Tegan],
TopFusion: Using Topological Feature Space for Fusion and Imputation in Multi-Modal Data,
TAG-PRA23(600-609)
IEEE DOI 2309
BibRef

Xue, Z.[Zihui], Marculescu, R.[Radu],
Dynamic Multimodal Fusion,
MULA23(2575-2584)
IEEE DOI 2309
BibRef

Li, X.[Xin], Ma, T.[Tao], Hou, Y.N.[Yue-Nan], Shi, B.[Botian], Yang, Y.C.[Yu-Chen], Liu, Y.[Youquan], Wu, X.J.[Xing-Jiao], Chen, Q.[Qin], Li, Y.[Yikang], Qiao, Y.[Yu], He, L.[Liang],
LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion,
CVPR23(17524-17534)
IEEE DOI 2309
BibRef

Kong, L.K.[Ling-Ke], Qi, X.S.[X. Sharon], Shen, Q.J.[Qi-Jin], Wang, J.C.[Jia-Cheng], Zhang, J.Y.[Jing-Yi], Hu, Y.[Yanle], Zhou, Q.C.[Qi-Chao],
Indescribable Multi-Modal Spatial Evaluator,
CVPR23(9853-9862)
IEEE DOI 2309

WWW Link. BibRef

Zhao, Z.X.[Zi-Xiang], Bai, H.W.[Hao-Wen], Zhang, J.S.[Jiang-She], Zhang, Y.[Yulun], Xu, S.[Shuang], Lin, Z.[Zudi], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion,
CVPR23(5906-5916)
IEEE DOI 2309
BibRef

Li, Y.[Yaowei], Quan, R.J.[Rui-Jie], Zhu, L.C.[Lin-Chao], Yang, Y.[Yi],
Efficient Multimodal Fusion via Interactive Prompting,
CVPR23(2604-2613)
IEEE DOI 2309
BibRef

Wetzer, E.[Elisabeth], Lindblad, J.[Joakim], Sladoje, N.[Nataša],
Can Representation Learning for Multimodal Image Registration be Improved by Supervision of Intermediate Layers?,
IbPRIA23(261-275).
Springer DOI 2307
BibRef

Huang, Z.B.[Zhan-Bo], Liu, J.Y.[Jin-Yuan], Fan, X.[Xin], Liu, R.S.[Ri-Sheng], Zhong, W.[Wei], Luo, Z.X.[Zhong-Xuan],
ReCoNet: Recurrent Correction Network for Fast and Efficient Multi-modality Image Fusion,
ECCV22(XVIII:539-555).
Springer DOI 2211
BibRef

Duan, J.L.[Jia-Li], Chen, L.Q.[Li-Qun], Tran, S.[Son], Yang, J.Y.[Jin-Yu], Xu, Y.[Yi], Zeng, B.[Belinda], Chilimbi, T.[Trishul],
Multi-modal Alignment using Representation Codebook,
CVPR22(15630-15639)
IEEE DOI 2210
Training, Representation learning, Image coding, Dictionaries, Benchmark testing, Vision + language BibRef

Xue, Z.H.[Zi-Hui], Ren, S.C.[Su-Cheng], Gao, Z.Q.[Zheng-Qi], Zhao, H.[Hang],
Multimodal Knowledge Expansion,
ICCV21(834-843)
IEEE DOI 2203
Multimodal sensors, Semisupervised learning, Data collection, Data models, Internet, Task analysis, Vision + other modalities, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Zolfaghari, M.[Mohammadreza], Zhu, Y.[Yi], Gehler, P.[Peter], Brox, T.[Thomas],
CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations,
ICCV21(1430-1439)
IEEE DOI 2203
Vision + language, Vision + other modalities BibRef

Piergiovanni, A.J., Casser, V.[Vincent], Ryoo, M.S.[Michael S.], Angelova, A.[Anelia],
4D-Net for Learned Multi-Modal Alignment,
ICCV21(15415-15425)
IEEE DOI 2203
Point cloud compression, Codes, Dynamics, Object detection, Sensors, Vision for robotics and autonomous vehicles, Detection and localization in 2D and 3D BibRef

Yang, J.H.[Jian-Hua], Huang, Y.[Yan], Ma, Z.Y.[Zhan-Yu], Wang, L.[Liang],
CMF: Cascaded Multi-Model Fusion for Referring Image Segmentation,
ICIP21(2289-2293)
IEEE DOI 2201
Convolutional codes, Image segmentation, Visualization, Fuses, Linguistics, Benchmark testing, Referring Image Segmentation, Context Modeling BibRef

Panda, R.[Rameswar], Chen, C.F.R.[Chun-Fu Richard], Fan, Q.F.[Quan-Fu], Sun, X.[Ximeng], Saenko, K.[Kate], Oliva, A.[Aude], Feris, R.S.[Rogerio S.],
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition,
ICCV21(7556-7565)
IEEE DOI 2203
Adaptation models, Computational modeling, Standards, Video analysis and understanding, BibRef

Shi, Z.S.[Zhen-Sheng], Liang, J.[Ju], Li, Q.Q.[Qian-Qian], Zheng, H.Y.[Hai-Yong], Gu, Z.R.[Zhao-Rui], Dong, J.Y.[Jun-Yu], Zheng, B.[Bing],
Multi-Modal Multi-Action Video Recognition,
ICCV21(13658-13667)
IEEE DOI 2203
Convolutional codes, Visualization, Analytical models, Computational modeling, Benchmark testing, Video analysis and understanding BibRef

Huang, S.C.[Shih-Cheng], Shen, L.Y.[Li-Yue], Lungren, M.P.[Matthew P.], Yeung, S.[Serena],
GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition,
ICCV21(3922-3931)
IEEE DOI 2203
Representation learning, Deep learning, Training, Image segmentation, Image recognition, Image analysis, Vision + language BibRef

Chen, B.[Brian], Rouditchenko, A.[Andrew], Duarte, K.[Kevin], Kuehne, H.[Hilde], Thomas, S.[Samuel], Boggust, A.[Angie], Panda, R.[Rameswar], Kingsbury, B.[Brian], Feris, R.S.[Rogerio S.], Harwath, D.[David], Glass, J.[James], Picheny, M.[Michael], Chang, S.F.[Shih-Fu],
Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos,
ICCV21(7992-8001)
IEEE DOI 2203
Training, Optical losses, Location awareness, Annotations, Semantics, Pipelines, Video analysis and understanding, Vision + other modalities BibRef

Liang, T.[Tao], Lin, G.S.[Guo-Sheng], Feng, L.[Lei], Zhang, Y.[Yan], Lv, F.M.[Feng-Mao],
Attention is not Enough: Mitigating the Distribution Discrepancy in Asynchronous Multimodal Sequence Fusion,
ICCV21(8128-8136)
IEEE DOI 2203
Correlation, Fuses, Computational modeling, Benchmark testing, Transformers, Acoustics, Video analysis and understanding, BibRef

Liu, Y.Z.[Yun-Ze], Fan, Q.N.[Qing-Nan], Zhang, S.H.[Shang-Hang], Dong, H.[Hao], Funkhouser, T.[Thomas], Yi, L.[Li],
Contrastive Multimodal Fusion with TupleInfoNCE,
ICCV21(734-743)
IEEE DOI 2203
Training, Representation learning, Benchmark testing, Task analysis, Optimization, Vision + other modalities, Representation learning BibRef

Ouerghi, H.[Hajer], Mourali, O.[Olfa], Zagrouba, E.[Ezzeddine],
Multi-modal Image Fusion Based on Weight Local Features and Novel Sum-modified-laplacian in Non-subsampled Shearlet Transform Domain,
ISVC20(II:166-179).
Springer DOI 2103
BibRef

Perez-Rua, J.M.[Juan-Manuel], Vielzeuf, V.[Valentin], Pateux, S.[Stephane], Baccouche, M.[Moez], Jurie, F.[Frederic],
MFAS: Multimodal Fusion Architecture Search,
CVPR19(6959-6968).
IEEE DOI 2002
BibRef

Sun, S.H.[Shan-Hui], Hu, J.[Jing], Yao, M.Q.[Ming-Qing], Hu, J.R.[Jin-Rong], Yang, X.D.[Xiao-Dong], Song, Q.[Qi], Wu, X.[Xi],
Robust Multimodal Image Registration Using Deep Recurrent Reinforcement Learning,
ACCV18(II:511-526).
Springer DOI 1906
BibRef

Vielzeuf, V.[Valentin], Lechervy, A.[Alexis], Pateux, S.[Stéphane], Jurie, F.[Frédéric],
CentralNet: A Multilayer Approach for Multimodal Fusion,
MultLearnApp18(VI:575-589).
Springer DOI 1905
BibRef

Son, C.H., Zhang, X.P.,
Multimodal fusion via a series of transfers for noise removal,
ICIP17(530-534)
IEEE DOI 1803
Image representation, Imaging, Pattern recognition, Visual communication, Near-infrared imaging, multimodal fusion BibRef

Shrivastava, A.[Ashish], Rastegari, M.[Mohammad], Shekhar, S.[Sumit], Chellappa, R.[Rama], Davis, L.S.[Larry S.],
Class consistent multi-modal fusion with binary features,
CVPR15(2282-2291)
IEEE DOI 1510
BibRef

Kasiri, K.[Keyvan], Fieguth, P.W.[Paul W.], Clausi, D.A.[David A.],
Self-similarity measure for multi-modal image registration,
ICIP16(4498-4502)
IEEE DOI 1610
BibRef
Earlier:
Structural Representations for Multi-modal Image Registration Based on Modified Entropy,
ICIAR15(82-89).
Springer DOI 1507
Brain. BibRef

Zhang, H.[Hong], Chen, L.[Li], Liu, J.[Jun], Yuan, J.S.[Jun-Song],
Hierarchical multi-feature fusion for multimodal data analysis,
ICIP14(5916-5920)
IEEE DOI 1502
Algorithm design and analysis BibRef

Shen, X.Y.[Xiao-Yong], Xu, L.[Li], Zhang, Q.[Qi], Jia, J.Y.[Jia-Ya],
Multi-modal and Multi-spectral Registration for Natural Images,
ECCV14(IV: 309-324).
Springer DOI 1408
BibRef

Sahoo, S., Nanda, P.K., Samant, S.,
Tsallis and Renyi's embedded entropy based mutual information for multimodal image registration,
NCVPRIPG13(1-4)
IEEE DOI 1408
biomedical MRI BibRef

Kim, M.J.[Min-Jae], Han, D.K.[David K.], Ko, H.S.[Han-Seok],
Multimodal image fusion via sparse representation with local patch dictionaries,
ICIP13(1301-1305)
IEEE DOI 1402
Dictionaries BibRef

Glodek, M.[Michael], Schels, M.[Martin], Palm, G.[Gunther], Schwenker, F.[Friedhelm],
Multi-modal Fusion based on classifiers using reject options and Markov Fusion Networks,
ICPR12(1084-1087).
WWW Link. 1302
BibRef

Forsberg, D.[Daniel], Farnebäck, G.[Gunnar], Knutsson, H.[Hans], Westin, C.F.[Carl-Fredrik],
Multi-modal Image Registration Using Polynomial Expansion and Mutual Information,
WBIR12(40-49).
Springer DOI 1208
BibRef

Bodensteiner, C., Huebner, W., Juengling, K., Mueller, J., Arens, M.,
Local multi-modal image matching based on self-similarity,
ICIP10(937-940).
IEEE DOI 1009
BibRef

Vegh, V.[Viktor], Yang, Z.Y.[Zheng-Yi], Tieng, Q.M.[Quang M.], Reutens, D.C.[David C.],
Multimodal image registration using stochastic differential equation optimization,
ICIP10(4385-4388).
IEEE DOI 1009
BibRef

Peng, T.Y.[Ting-Ying], Yigitsoy, M.[Mehmet], Eslami, A.[Abouzar], Bayer, C.[Christine], Navab, N.[Nassir],
Deformable Registration of Multi-modal Microscopic Images Using a Pyramidal Interactive Registration-Learning Methodology,
WBIR14(144-153).
Springer DOI 1407
BibRef

Wachinger, C.[Christian], Navab, N.[Nassir],
Manifold Learning for Multi-modal Image Registration,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Xu, J.[Jiang], Yuan, J.S.[Jun-Song], Wu, Y.[Ying],
Multimodal Partial Estimates Fusion,
ICCV09(2177-2184).
IEEE DOI
PDF File. 0909
BibRef

Ma, W.Y.[Wen-Ying], Li, S.[Sheng], Yao, Y.F.[Yong-Fang], Lan, C.[Chao], Gao, S.Q.[Shi-Qiang], Tang, H.[Hui], Jing, X.Y.[Xiao-Yuan],
Multi-Modal Biometrics Pixel Level Fusion and KPCA-RBF Feature Classification for Single Sample Recognition Problem,
CISP09(1-5).
IEEE DOI 0910
BibRef

Town, C.[Christopher], Zhu, Z.G.[Zhi-Gang],
Sensor Fusion and Environmental Modelling for Multimodal Sentient Computing,
MSCSAS07(1-2).
IEEE DOI 0706
BibRef

Datar, M., Gopalakrishnan, G., Ranjan, S., Mullick, R.,
Anatomically Guided Registration for Multimodal Images,
AIPR06(10-10).
IEEE DOI 0610
BibRef

Gopalakrishnan, G., Kumar, S.V.B., Narayanan, A., Mullick, R.,
A fast piecewise deformable method for multi-modality image registration,
AIPR05(114-119).
IEEE DOI 0510
BibRef

Kelman, A.[Avi], Sofka, M.[Michal], Stewart, C.V.[Charles V.],
Keypoint Descriptors for Matching Across Multiple Image Modalities and Non-linear Intensity Variations,
Fusion07(1-7).
IEEE DOI 0706
BibRef

Guo, Y.J.[Yu-Jun], Lu, C.C.[Cheng-Chang],
Multi-modality Image Registration Using Mutual Information Based on Gradient Vector Flow,
ICPR06(III: 697-700).
IEEE DOI 0609
BibRef

Andronache, A.[Adrian], Cattin, P.C.[Philippe C.], Székely, G.[Gábor],
Local Intensity Mapping for Hierarchical Non-rigid Registration of Multi-modal Images Using the Cross-Correlation Coefficient,
WBIR06(26-33).
Springer DOI 0607
BibRef

Cremers, D.[Daniel], Guetter, C.[Christoph], Xu, C.Y.[Chen-Yang],
Nonparametric Priors on the Space of Joint Intensity Distributions for Non-Rigid Multi-Modal Image Registration,
CVPR06(II: 1777-1783).
IEEE DOI 0606
BibRef

Zöllei, L.[Lilla], Wells, III, W.M.[William M.],
Multi-modal Image Registration Using Dirichlet-Encoded Prior Information,
WBIR06(34-42).
Springer DOI 0607
BibRef

Zollei, L.[Lilla], Fisher, J.[John], Wells, III, W.M.[William M.],
A Unified Statistical and Information Theoretic Framework for Multi-modal Image Registration,
MIT AIM-2004-011, April 28, 2004.
WWW Link. 0501
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Chan, H.M.[Ho-Ming], Chung, A.C.S., Yu, S.C.H., Norbash, A., Wells, III, W.M.[William M.],
Multi-modal image registration by minimizing Kullback-Leibler distance between expected and observed joint class histograms,
CVPR03(II: 570-576).
IEEE DOI 0307
BibRef

Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Fusion, Range or Depth and Intensity or Color Data .

Last update:Jul 7, 2025 at 14:35:55