{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T15:41:56Z","timestamp":1784821316543,"version":"3.55.0"},"reference-count":170,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2025YFF0515600"],"award-info":[{"award-number":["2025YFF0515600"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["624B2100"],"award-info":[{"award-number":["624B2100"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Fusion"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.inffus.2026.104437","type":"journal-article","created":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T22:25:08Z","timestamp":1777674308000},"page":"104437","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":11,"special_numbering":"C","title":["Multimodal fusion on low-quality data: A comprehensive survey"],"prefix":"10.1016","volume":"135","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-3995-2062","authenticated-orcid":false,"given":"Qingyang","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yake","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zongbo","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huazhu","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinghua","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Deng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cai","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Wen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changqing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.inffus.2026.104437_bib0001","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2106235118","article-title":"How multisensory neurons solve causal inference","volume":"118","author":"Rideaux","year":"2021","journal-title":"Proc. Natl. Acad. Sci."},{"key":"10.1016\/j.inffus.2026.104437_bib0002","series-title":"2022 International Conference on Robotics and Automation (ICRA)","article-title":"Fast road segmentation via uncertainty-aware symmetric network","author":"Chang","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0003","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1109\/TITS.2020.3013234","article-title":"Multimodal end-to-end autonomous driving","volume":"23","author":"Xiao","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0004","doi-asserted-by":"crossref","first-page":"15:1","DOI":"10.1145\/3517139","article-title":"A deep multi-level attentive network for multimodal sentiment analysis","volume":"19","author":"Yadav","year":"2023","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl."},{"key":"10.1016\/j.inffus.2026.104437_bib0005","series-title":"MultiMedia Modeling: 22nd International Conference, MMM 2016, Miami, FL, USA, January 4\u20136, 2016, Proceedings, Part II 22","article-title":"Sentiment analysis on multi-view social data","author":"Niu","year":"2016"},{"key":"10.1016\/j.inffus.2026.104437_bib0006","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"Multi-interactive memory network for aspect based multimodal sentiment analysis","author":"Xu","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0007","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"What makes training multi-modal classification networks hard?","author":"Wang","year":"2020"},{"key":"10.1016\/j.inffus.2026.104437_bib0008","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Balanced multimodal learning via on-the-fly gradient modulation","author":"Peng","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0009","series-title":"International Conference on Machine Learning","article-title":"Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks","author":"Wu","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0010","series-title":"International Conference on Machine Learning","article-title":"Modality competition: what makes joint training of multi-modal network fail in deep learning?(provably)","author":"Huang","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0011","series-title":"Proceedings of the 29th International Conference on Computational Linguistics","article-title":"Different data, different modalities! reinforced data splitting for effective multimodal information extraction from social media posts","author":"Xu","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0012","article-title":"Learning with noisy correspondence for cross-modal matching","author":"Huang","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0013","unstructured":"C. Xu, D. Tao, C. Xu, A survey on multi-view learning, arXiv preprint arXiv: 1304.5634(2013)."},{"key":"10.1016\/j.inffus.2026.104437_bib0014","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1109\/TPAMI.2018.2798607","article-title":"Multimodal machine learning: a survey and taxonomy","volume":"41","author":"Baltru\u0161aitis","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0015","doi-asserted-by":"crossref","first-page":"1136","DOI":"10.1109\/TSMC.2022.3192635","article-title":"A survey on incomplete multiview clustering","volume":"53","author":"Wen","year":"2022","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0016","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.inffus.2020.01.003","article-title":"Pixel level fusion techniques for SAR and optical images: a review","volume":"59","author":"Kulkarni","year":"2020","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.inffus.2026.104437_bib0017","series-title":"IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16\u201320, 2019","article-title":"Noise-aware unsupervised deep lidar-Stereo fusion","author":"Cheng","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0018","article-title":"Multi-modality approaches for medical support systems: a systematic review of the last decade","author":"Salvi","year":"2023","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.inffus.2026.104437_bib0019","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18\u201324, 2022","article-title":"TransFusion: robust liDAR-camera fusion for 3D object detection with transformers","author":"Bai","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0020","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/LSP.2007.911148","article-title":"Variational models for fusion and denoising of multifocus images","volume":"15","author":"Wang","year":"2008","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.inffus.2026.104437_bib0021","doi-asserted-by":"crossref","first-page":"2137","DOI":"10.1109\/TIP.2009.2025006","article-title":"A total variation-based algorithm for pixel-level image fusion","volume":"18","author":"Kumar","year":"2009","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.inffus.2026.104437_bib0022","first-page":"225","article-title":"A novel medical image fusion by combining TV-L1 decomposed textures based on adaptive weighting scheme","volume":"23","author":"Padmavathi","year":"2020","journal-title":"Eng. Sci. Technol. Int. J."},{"key":"10.1016\/j.inffus.2026.104437_bib0023","doi-asserted-by":"crossref","first-page":"1460","DOI":"10.1109\/TMM.2021.3065496","article-title":"A total variation with joint norms for infrared and visible image fusion","volume":"24","author":"Nie","year":"2021","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.inffus.2026.104437_bib0024","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.3390\/rs13061143","article-title":"Relative total variation structure analysis-based fusion method for hyperspectral and LiDAR data classification","volume":"13","author":"Quan","year":"2021","journal-title":"Remote Sens."},{"key":"10.1016\/j.inffus.2026.104437_bib0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.dsp.2022.103387","article-title":"TSE_Fuse: two stage enhancement method using attention mechanism and feature-linking model for infrared and visible image fusion","volume":"123","author":"Liu","year":"2022","journal-title":"Digit. Signal Process."},{"key":"10.1016\/j.inffus.2026.104437_bib0026","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Conceptual 12m: pushing web-scale image-text pre-training to recognize long-tail visual concepts","author":"Changpinyo","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0027","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","article-title":"Weakly aligned cross-modal learning for multispectral pedestrian detection","author":"Zhang","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0028","series-title":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","article-title":"Conceptual captions: a cleaned, hypernymed, image alt-text dataset for automatic image captioning","author":"Sharma","year":"2018"},{"key":"10.1016\/j.inffus.2026.104437_bib0029","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Filtering, distillation, and hard negatives for vision-language pre-training","author":"Radenovic","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0030","doi-asserted-by":"crossref","DOI":"10.52202\/075280-1179","article-title":"Datacomp: in search of the next generation of multimodal datasets","author":"Gadre","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0031","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S1361-8415(01)80026-8","article-title":"A survey of medical image registration","volume":"2","author":"Maintz","year":"1998","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.inffus.2026.104437_bib0032","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1016\/S0262-8856(03)00137-9","article-title":"Image registration methods: a survey","volume":"21","author":"Zitova","year":"2003","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.inffus.2026.104437_bib0033","article-title":"Align before fuse: vision and language representation learning with momentum distillation","author":"Li","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0034","series-title":"International Conference on Machine Learning","article-title":"Blip: bootstrapping language-image pre-training for unified vision-language understanding and generation","author":"Li","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0035","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"Nlip: noise-robust language-image pre-training","author":"Huang","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0036","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XXX 16","article-title":"Oscar: object-semantics aligned pre-training for vision-language tasks","author":"Li","year":"2020"},{"key":"10.1016\/j.inffus.2026.104437_bib0037","series-title":"International Conference on Artificial Intelligence and Statistics","article-title":"Understanding multimodal contrastive learning and incorporating unpaired data","author":"Nakada","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0038","series-title":"International Conference on Machine Learning","article-title":"Learning transferable visual models from natural language supervision","author":"Radford","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0039","series-title":"Advances in Neural Information Processing Systems","article-title":"Visual instruction tuning","author":"Liu","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0040","series-title":"International Conference on Representation Learning","article-title":"Llama-adapter: efficient fine-tuning of language models with zero-init attention","author":"Gao","year":"2024"},{"key":"10.1016\/j.inffus.2026.104437_bib0041","doi-asserted-by":"crossref","DOI":"10.1109\/TIM.2017.2700198","article-title":"Medical image fusion and denoising with alternating sequential filter and adaptive fractional order total variation","author":"Zhao","year":"2017","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.inffus.2026.104437_bib0042","series-title":"International Conference on Machine Learning","article-title":"BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large language models","author":"Li","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0043","series-title":"IEEE International Conference on Data Mining","article-title":"Clustering on multiple incomplete datasets via collective kernel learning","author":"Shao","year":"2013"},{"key":"10.1016\/j.inffus.2026.104437_bib0044","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1016\/j.neuroimage.2011.09.069","article-title":"Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer\u2019s disease","volume":"59","author":"Zhang","year":"2012","journal-title":"NeuroImage"},{"key":"10.1016\/j.inffus.2026.104437_bib0045","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1016\/j.neuroimage.2013.09.015","article-title":"Inter-modality relationship constrained multi-modality multi-task feature selection for Alzheimer\u2019s disease and mild cognitive impairment identification","volume":"84","author":"Liu","year":"2014","journal-title":"NeuroImage"},{"key":"10.1016\/j.inffus.2026.104437_bib0046","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1016\/j.neuroimage.2014.01.033","article-title":"Neurodegenerative disease diagnosis using incomplete multi-modality data via matrix shrinkage and completion","volume":"91","author":"Thung","year":"2014","journal-title":"NeuroImage"},{"key":"10.1016\/j.inffus.2026.104437_bib0047","series-title":"Proceedings of the 2015th European Conference on Machine Learning and Knowledge Discovery in Databases-Volume Part I","article-title":"Multiple incomplete views clustering via weighted nonnegative matrix factorization with L 2, 1 regularization","author":"Shao","year":"2015"},{"key":"10.1016\/j.inffus.2026.104437_bib0048","series-title":"Proceedings of the International Joint Conference on Artificial Intelligence","article-title":"Incomplete multi-modal visual data grouping","author":"Zhao","year":"2016"},{"key":"10.1016\/j.inffus.2026.104437_bib0049","series-title":"IEEE International Conference on Big Data (Big Data)","article-title":"Online multi-view clustering with incomplete views","author":"Shao","year":"2016"},{"key":"10.1016\/j.inffus.2026.104437_bib0050","series-title":"Proceedings of the International Joint Conference on Artificial Intelligence","article-title":"Spectral perturbation meets incomplete multi-view data","author":"Wang","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0051","series-title":"IFIP TC 12 International Conference on Intelligent Information Processing VIII","article-title":"Incomplete multi-view clustering","author":"Gao","year":"2016"},{"key":"10.1016\/j.inffus.2026.104437_bib0052","series-title":"Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining","article-title":"Consensus graph learning for incomplete multi-view clustering","author":"Zhou","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0053","series-title":"International Conference on Machine Learning Workshop on Learning with Multiple Views","article-title":"Analytical kernel matrix completion with incomplete multi-view data","author":"Williams","year":"2005"},{"key":"10.1016\/j.inffus.2026.104437_bib0054","series-title":"Annual Conference on Neural Information Processing Systems Workshop on Machine Learning for Social Computing","article-title":"Multiview clustering with incomplete views","author":"Trivedi","year":"2010"},{"key":"10.1016\/j.inffus.2026.104437_bib0055","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1007\/s10994-016-5618-0","article-title":"Multi-view kernel completion","volume":"106","author":"Bhadra","year":"2017","journal-title":"Mach. Learn."},{"key":"10.1016\/j.inffus.2026.104437_bib0056","series-title":"IJCAI","article-title":"Semi-supervised multi-modal learning with incomplete modalities","author":"Yang","year":"2018"},{"key":"10.1016\/j.inffus.2026.104437_bib0057","doi-asserted-by":"crossref","DOI":"10.1109\/TPAMI.2019.2892416","article-title":"Multiple kernel k k-means with incomplete kernels","author":"Liu","year":"2019","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0058","doi-asserted-by":"crossref","DOI":"10.1155\/2017\/3961718","article-title":"Consensus kernel K-means clustering for incomplete multiview data","author":"Ye","year":"2017","journal-title":"Comput. Intell. Neurosci."},{"key":"10.1016\/j.inffus.2026.104437_bib0059","series-title":"International Joint Conference on Artificial Intelligence","article-title":"Localized incomplete multiple kernel k-means","author":"Zhu","year":"2018"},{"key":"10.1016\/j.inffus.2026.104437_bib0060","article-title":"Incomplete multiple kernel alignment maximization for clustering","author":"Liu","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0061","doi-asserted-by":"crossref","first-page":"2493","DOI":"10.1109\/TMM.2020.3013408","article-title":"Adaptive graph completion based incomplete multi-view clustering","volume":"23","author":"Wen","year":"2021","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.inffus.2026.104437_bib0062","series-title":"IEEE International Conference on Big Data","article-title":"VIGAN: missing view imputation with generative adversarial networks","author":"Shang","year":"2017"},{"key":"10.1016\/j.inffus.2026.104437_bib0063","series-title":"IEEE International Conference on Data Mining","article-title":"Partial multi-view clustering via consistent GAN","author":"Wang","year":"2018"},{"key":"10.1016\/j.inffus.2026.104437_bib0064","series-title":"International Joint Conference on Artificial Intelligence","article-title":"Adversarial incomplete multi-view clustering","author":"Xu","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0065","article-title":"Generative incomplete multi-view prognosis predictor for breast cancer: GIMPP","author":"Arya","year":"2021","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"10.1016\/j.inffus.2026.104437_bib0066","series-title":"IEEE Conference on Computer Vision and Pattern Recognition","article-title":"Missing modalities imputation via cascaded residual autoencoder","author":"Tran","year":"2017"},{"key":"10.1016\/j.inffus.2026.104437_bib0067","article-title":"Information recovery-driven deep incomplete multiview clustering network","author":"Liu","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0068","series-title":"International Conference on Machine Learning","article-title":"Deep safe incomplete multi-view clustering: theorem and algorithm","author":"Tang","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0069","doi-asserted-by":"crossref","DOI":"10.1109\/TPAMI.2022.3197238","article-title":"Dual contrastive prediction for incomplete multi-view representation learning","author":"Lin","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0070","series-title":"AAAI Conference on Artificial Intelligence","article-title":"Unified embedding alignment with missing views inferring for incomplete multi-view clustering","author":"Wen","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0071","doi-asserted-by":"crossref","DOI":"10.1109\/TKDE.2021.3112114","article-title":"Incomplete multi-view clustering with reconstructed views","author":"Yin","year":"2021","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.inffus.2026.104437_bib0072","series-title":"AAAI Conference on Artificial Intelligence","article-title":"Unified tensor framework for incomplete multi-view clustering and missing-view inferring","author":"Wen","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0073","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Exploring and exploiting uncertainty for incomplete multi-view classification","author":"Xie","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0074","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Completer: incomplete multi-view clustering via contrastive prediction","author":"Lin","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0075","article-title":"Partial multiview representation learning with cross-view generation","author":"Dong","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0076","article-title":"Robust multi-view clustering with incomplete information","author":"Yang","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0077","series-title":"Proceedings of the 32th International Joint Conference on Artificial Intelligence","article-title":"Incomplete multi-view clustering via prototype-based imputation","author":"Li","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0078","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102357","article-title":"A novel federated multi-view clustering method for unaligned and incomplete data fusion","author":"Ren","year":"2024","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.inffus.2026.104437_bib0079","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"Partial multi-view clustering","author":"Li","year":"2014"},{"key":"10.1016\/j.inffus.2026.104437_bib0080","series-title":"Proceedings of the ACM International Conference on Multimedia","article-title":"Partial multi-view subspace clustering","author":"Xu","year":"2018"},{"key":"10.1016\/j.inffus.2026.104437_bib0081","article-title":"Latent representation learning for Alzheimer\u2019s disease diagnosis with incomplete multi-modality neuroimaging and genetic data","author":"Zhou","year":"2019","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.inffus.2026.104437_bib0082","series-title":"Proceedings of the International Joint Conference on Artificial Intelligence","article-title":"Doubly aligned incomplete multi-view clustering","author":"Hu","year":"2018"},{"key":"10.1016\/j.inffus.2026.104437_bib0083","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"One-pass incomplete multi-view clustering","author":"Hu","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0084","article-title":"Localized sparse incomplete multi-view clustering","author":"Liu","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.inffus.2026.104437_bib0085","article-title":"Generalized incomplete multiview clustering with flexible locality structure diffusion","author":"Wen","year":"2020","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.inffus.2026.104437_bib0086","article-title":"Projective incomplete multi-view clustering","author":"Deng","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0087","article-title":"A concise yet effective model for non-aligned incomplete multi-view and missing multi-label learning","author":"Li","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0088","series-title":"Proceedings of the 27th International Joint Conference on Artificial Intelligence","article-title":"Incomplete multi-view weak-label learning","author":"Tan","year":"2018"},{"key":"10.1016\/j.inffus.2026.104437_bib0089","article-title":"Infant brain development prediction with latent partial multi-view representation learning","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.inffus.2026.104437_bib0090","doi-asserted-by":"crossref","DOI":"10.1109\/TCYB.2018.2884715","article-title":"Incomplete multiview spectral clustering with adaptive graph learning","author":"Wen","year":"2020","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.inffus.2026.104437_bib0091","series-title":"Pacific Rim International Conference on Artificial Intelligence","article-title":"Incomplete multi-view clustering via structured graph learning","author":"Wu","year":"2018"},{"key":"10.1016\/j.inffus.2026.104437_bib0092","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Highly confident local structure based consensus graph learning for incomplete multi-view clustering","author":"Wen","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0093","series-title":"Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","article-title":"Multi-source learning with block-wise missing data for alzheimer\u2019s disease prediction","author":"Xiang","year":"2013"},{"key":"10.1016\/j.inffus.2026.104437_bib0094","article-title":"View-aligned hypergraph learning for Alzheimer\u2019s disease diagnosis with incomplete multi-modality data","author":"Liu","year":"2017","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.inffus.2026.104437_bib0095","article-title":"Late fusion incomplete multi-view clustering","author":"Liu","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0096","doi-asserted-by":"crossref","DOI":"10.1109\/TPAMI.2020.2974828","article-title":"Efficient and effective regularized incomplete multi-view clustering","author":"Liu","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0097","series-title":"Proceedings of the 29th ACM International Conference on Multimedia","article-title":"One-stage incomplete multi-view clustering via late fusion","author":"Zhang","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0098","article-title":"Incomplete multi-view clustering via deep semantic mapping","author":"Zhao","year":"2018","journal-title":"Neurocomputing"},{"key":"10.1016\/j.inffus.2026.104437_bib0099","series-title":"Proceedings of the 28th ACM International Conference on Multimedia","article-title":"Dimc-net: deep incomplete multi-view clustering network","author":"Wen","year":"2020"},{"key":"10.1016\/j.inffus.2026.104437_bib0100","series-title":"International Joint Conference on Artificial Intelligence","article-title":"CDIMC-net: cognitive deep incomplete multi-view clustering network","author":"Wen","year":"2020"},{"key":"10.1016\/j.inffus.2026.104437_bib0101","series-title":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","article-title":"Structural deep incomplete multi-view clustering network","author":"Wen","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0102","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"DICNet: deep instance-level contrastive network for double incomplete multi-view multi-label classification","author":"Liu","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0103","series-title":"AAAI Conference on Artificial Intelligence","article-title":"Deep incomplete multi-view clustering via mining cluster complementarity","author":"Xu","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0104","series-title":"Advances in Neural Information Processing Systems","article-title":"CPM-Nets: cross partial multi-view networks","author":"Zhang","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0105","article-title":"Deep double incomplete multi-view multi-label learning with incomplete labels and missing views","author":"Wen","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0106","series-title":"International Conference on Machine Learning","article-title":"Robustness in multimodal learning under train-test modality mismatch","author":"McKinzie","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0107","series-title":"Medical Imaging with Deep Learning","article-title":"Mmcformer: missing modality compensation transformer for brain tumor segmentation","author":"Karimijafarbigloo","year":"2024"},{"key":"10.1016\/j.inffus.2026.104437_bib0108","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"DrFuse: learning disentangled representation for clinical multi-modal fusion with missing modality and modal inconsistency","author":"Yao","year":"2024"},{"key":"10.1016\/j.inffus.2026.104437_bib0109","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btac643","article-title":"Lung cancer subtype diagnosis using weakly-paired multi-omics data","author":"Wang","year":"2022","journal-title":"Bioinformatics"},{"key":"10.1016\/j.inffus.2026.104437_bib0110","doi-asserted-by":"crossref","DOI":"10.1109\/TNNLS.2020.3027729","article-title":"Flexible cross-modal hashing","author":"Yu","year":"2022","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0111","article-title":"Partially view-aligned representation learning via cross-view graph contrastive network","author":"Wang","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.inffus.2026.104437_bib0112","series-title":"Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence","article-title":"Weakly-supervised multi-view multi-instance multi-label learning","author":"Xing","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0113","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"MaPLe: multi-modal prompt learning","author":"Khattak","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0114","series-title":"International Journal of Computer Vision","article-title":"Learning to prompt for vision-language models","author":"Zhou","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0115","unstructured":"W. Kay, J. Carreira, K. Simonyan, B. Zhang, C. Hillier, S. Vijayanarasimhan, F. Viola, T. Green, T. Back, P. Natsev, et al., The kinetics human action video dataset, arXiv preprint arXiv: 1705.06950(2017)."},{"key":"10.1016\/j.inffus.2026.104437_bib0116","article-title":"Deep multimodal fusion by channel exchanging","author":"Wang","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0117","unstructured":"F. Xiao, Y.J. Lee, K. Grauman, J. Malik, C. Feichtenhofer, Audiovisual slowfast networks for video recognition, arXiv preprint arXiv: 2001.08740(2020)."},{"key":"10.1016\/j.inffus.2026.104437_bib0118","doi-asserted-by":"crossref","DOI":"10.1109\/LSP.2021.3101421","article-title":"Learning to balance the learning rates between various modalities via adaptive tracking factor","author":"Sun","year":"2021","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.inffus.2026.104437_bib0119","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","article-title":"Joint audio-visual deepfake detection","author":"Zhou","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0120","article-title":"MCL: a contrastive learning method for multimodal data fusion in violence detection","author":"Yang","year":"2022","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.inffus.2026.104437_bib0121","series-title":"International Conference on Machine Learning","article-title":"On uni-modal feature learning in supervised multi-modal learning","author":"Du","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0122","series-title":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","article-title":"Multimodal pre-training with self-distillation for product understanding in E-Commerce","author":"Liu","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0123","series-title":"ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","article-title":"Mmcosine: multi-modal cosine loss towards balanced audio-visual fine-grained learning","author":"Xu","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0124","series-title":"The Twelfth International Conference on Learning Representations","article-title":"Quantifying and enhancing multi-modal robustness with modality preference","author":"Yang","year":"2024"},{"key":"10.1016\/j.inffus.2026.104437_bib0125","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"PMR: Prototypical modal rebalance for multimodal learning","author":"Fan","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0126","series-title":"Proceedings of the 2023 ACM International Conference on Multimedia Retrieval","article-title":"Graph interactive network with adaptive gradient for multi-modal rumor detection","author":"Sun","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0127","article-title":"Multimodal imbalance-aware gradient modulation for weakly-supervised audio-visual video parsing","author":"Fu","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.inffus.2026.104437_bib0128","series-title":"Proceedings of the 3rd International on Multimodal Sentiment Analysis Workshop and Challenge","article-title":"Multimodal temporal attention in sentiment analysis","author":"He","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0129","article-title":"Utilizing greedy nature for multimodal conditional image synthesis in transformers","author":"Su","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.inffus.2026.104437_bib0130","unstructured":"B. Lin, Z. Lin, Y. Guo, Y. Zhang, J. Zou, S. Fan, Variational probabilistic fusion network for RGB-T semantic segmentation, arXiv preprint arXiv: 2307.08536(2023)."},{"key":"10.1016\/j.inffus.2026.104437_bib0131","series-title":"ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","article-title":"Adaptive mask co-Optimization for modal dependence in multimodal learning","author":"Zhou","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0132","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Enhancing multimodal cooperation via sample-level modality valuation","author":"Wei","year":"2024"},{"key":"10.1016\/j.inffus.2026.104437_bib0133","article-title":"On-the-fly modulation for balanced multimodal learning","author":"Wei","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0134","series-title":"ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","article-title":"Vggsound: a large-scale audio-visual dataset","author":"Chen","year":"2020"},{"key":"10.1016\/j.inffus.2026.104437_bib0135","series-title":"International Conference on Machine Learning","article-title":"Calibrating multimodal learning","author":"Ma","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0136","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XVIII 16","article-title":"Improving multispectral pedestrian detection by addressing modality imbalance problems","author":"Zhou","year":"2020"},{"key":"10.1016\/j.inffus.2026.104437_bib0137","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2018.11.017","article-title":"Fusion of multispectral data through illumination-aware deep neural networks for pedestrian detection","author":"Guan","year":"2019","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.inffus.2026.104437_bib0138","article-title":"DenseFuse: a fusion approach to infrared and visible images","author":"Li","year":"2018","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.inffus.2026.104437_bib0139","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","article-title":"Adamml: adaptive multi-modal learning for efficient video recognition","author":"Panda","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0140","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Dynamic multimodal fusion","author":"Xue","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0141","series-title":"ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","article-title":"Multimodal cross-and self-attention network for speech emotion recognition","author":"Sun","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0142","series-title":"2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)","article-title":"Self-attentive feature-level fusion for multimodal emotion detection","author":"Hazarika","year":"2018"},{"key":"10.1016\/j.inffus.2026.104437_bib0143","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"MMTM: multimodal transfer module for CNN fusion","author":"Joze","year":"2020"},{"key":"10.1016\/j.inffus.2026.104437_bib0144","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Multimodal object detection by channel switching and spatial attention","author":"Cao","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0145","article-title":"Attention bottlenecks for multimodal fusion","author":"Nagrani","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0146","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Omnivore: a single model for many visual modalities","author":"Girdhar","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0147","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Multimodal token fusion for vision transformers","author":"Wang","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0148","series-title":"2020 IEEE International Conference on Robotics and Automation (ICRA)","article-title":"UNO: uncertainty-aware noisy-or multimodal fusion for unanticipated input degradation","author":"Tian","year":"2020"},{"key":"10.1016\/j.inffus.2026.104437_bib0149","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Multimodal representation learning by alternating unimodal adaptation","author":"Zhang","year":"2024"},{"key":"10.1016\/j.inffus.2026.104437_bib0150","article-title":"Provable dynamic fusion for low-quality multimodal data","author":"Zhang","year":"2023","journal-title":"Int. Conf. Mach. Learn."},{"key":"10.1016\/j.inffus.2026.104437_bib0151","series-title":"Computer Vision\u2013ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part IX","article-title":"Multimodal object detection via probabilistic ensembling","author":"Chen","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0152","series-title":"International Conference on Representation Learning","article-title":"Trusted multi-view classification","author":"Han","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0153","article-title":"Confidence-aware fusion using dempster-shafer theory for multispectral pedestrian detection","author":"Li","year":"2022","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.inffus.2026.104437_bib0154","article-title":"Trusted multi-scale classification framework for whole slide image","author":"Feng","year":"2022","journal-title":"Biomed. Signal Process. Control"},{"key":"10.1016\/j.inffus.2026.104437_bib0155","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"Trusted multi-view deep learning with opinion aggregation","author":"Liu","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0156","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"Uncertainty-aware multi-view representation learning","author":"Geng","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0157","article-title":"COLD Fusion: calibrated and ordinal latent distribution fusion for uncertainty-Aware multimodal emotion recognition","author":"Tellamekala","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2026.104437_bib0158","series-title":"Advances in Neural Information Processing Systems","article-title":"Trustworthy multimodal regression with mixture of normal-inverse gamma distributions","author":"Ma","year":"2021"},{"key":"10.1016\/j.inffus.2026.104437_bib0159","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Multimodal dynamics: dynamical fusion for trustworthy multimodal classification","author":"Han","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0160","series-title":"The Twelfth International Conference on Learning Representations","article-title":"Test-time adaption against multi-modal reliability bias","author":"Yang","year":"2023"},{"key":"10.1016\/j.inffus.2026.104437_bib0161","article-title":"Stabilizing multispectral pedestrian detection with evidential hybrid fusion","author":"Li","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.inffus.2026.104437_bib0162","series-title":"2022 IEEE International Conference on Bioinformatics and Biomedicine (M)","article-title":"Uncertainty-based fusion netwok for automatic skin lesion diagnosis","author":"Chen","year":"2022"},{"key":"10.1016\/j.inffus.2026.104437_bib0163","series-title":"International Conference on Representation Learning","article-title":"A baseline for detecting misclassified and out-of-distribution examples in neural networks","author":"Hendrycks","year":"2017"},{"key":"10.1016\/j.inffus.2026.104437_bib0164","article-title":"Addressing failure prediction by learning model confidence","author":"Corbi\u00e8re","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0165","article-title":"What makes multi-modal learning better than single (provably)","author":"Huang","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.inffus.2026.104437_bib0166","series-title":"International Conference on Representation Learning","article-title":"Benchmarking neural network robustness to common corruptions and perturbations","author":"Hendrycks","year":"2019"},{"key":"10.1016\/j.inffus.2026.104437_bib0167","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v32i1.12024","article-title":"Multi-attention recurrent network for human communication comprehension","author":"Zadeh","year":"2018","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"10.1016\/j.inffus.2026.104437_bib0168","series-title":"Multimodal Grand Challenge at ICMI","article-title":"Multimodal sentiment analysis using the fused MOSI dataset","author":"Zadeh","year":"2016"},{"key":"10.1016\/j.inffus.2026.104437_bib0169","series-title":"European Conference on Computer Vision","article-title":"Indoor segmentation and support inference from rgbd images","author":"Silberman","year":"2012"},{"key":"10.1016\/j.inffus.2026.104437_bib0170","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Multispectral pedestrian detection: benchmark dataset and baseline","author":"Hwang","year":"2015"}],"container-title":["Information Fusion"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1566253526003179?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1566253526003179?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T23:34:22Z","timestamp":1783208062000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1566253526003179"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":170,"alternative-id":["S1566253526003179"],"URL":"https:\/\/doi.org\/10.1016\/j.inffus.2026.104437","relation":{},"ISSN":["1566-2535"],"issn-type":[{"value":"1566-2535","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Multimodal fusion on low-quality data: A comprehensive survey","name":"articletitle","label":"Article Title"},{"value":"Information Fusion","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.inffus.2026.104437","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"104437"}}