Deep multimodal fusion for semantic image segmentation: A survey
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Some recent surveys focus primarily on traditional perception tasks such as semantic segmentation or 3D object detection, lacking a systematic review of deep learning-driven cross-modal modeling.
“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]
The Introduction identifies semantic image segmentation as this survey’s focus. But the Conclusion says it categorizes 20 deep multimodal fusion methods and discusses their architectural design, so the claim that it lacks a systematic review of deep-learning-driven cross-modal approaches is too broad. Its review is limited to semantic image segmentation. (LLM, conf=0.86)
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- 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 · 2020: 1
- 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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