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Deep multimodal fusion for semantic image segmentation: A survey
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“Some surveys primarily focus on traditional perception tasks such as semantic segmentation [27] or 3D object detection [28], lacking a systematic review of deep learning-driven cross-modal modeling approaches.”
From Multimodal fusion and vision–language models: A survey for robot vision (2026) · cites this paper as [27]
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Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
ImageNet: A large-scale hierarchical image database
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Microsoft COCO: Common Objects in Context
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Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298965 · Cited by 38,834
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
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- Chen, 2018, 40, 834
- Gade, 2014, Thermal cameras and applications: a survey, Mach. Vision Appl., 25, 245, 10.1007/s00138-013-0570-5 · DOI · Paper page
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Zhao, F., Zhang, C., & Geng, B. (2024) · ACM Computing Surveys · doi:10.1145/3649447 · Cited by 480
Tang, L., Zhang, H., Xu, H., & Ma, J. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.101870 · Cited by 418
A review on 2D instance segmentation based on deep neural networks
Gu, W., Bai, S., & Kong, L. (2022) · Image and Vision Computing · doi:10.1016/j.imavis.2022.104401 · Cited by 258
Hosseinpour, H., Samadzadegan, F., & Javan, F. D. (2021) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2021.12.007 · Cited by 233
Shaik, T., Tao, X., Li, L., Xie, H., & Velasquez, J. D. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.102040 · Cited by 228
Metadata
- Authors
- Zhang, Y., Sidibé, D., Morel, O., & Mériaudeau, F.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Zhang, Yifei
- Venue
- Image and Vision Computing
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 105
- Pages
- 104042
- ISSN
- 0262-8856 (ISSN-L)
- OpenAlex
- W3091791645
- Cited by
- 261
- References
- 181
- Citations by year
- 2026: 28 · 2025: 83 · 2024: 59 · 2023: 49 · 2022: 26 · 2021: 15
- FWCI
- 8.85
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- Image and Vision Computing (publishedVersion)
- HAL (submittedVersion, other-oa)
- Funders
- Agence Nationale de la Recherche
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Engineering › Media Technology › Advanced Image Fusion Techniques
- Keywords
- multimodal fusion, semantic segmentation, feature-level fusion, decision fusion, hybrid fusion, fusion strategies, scene understanding
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