CM2-STNet: Cross-modal image matching with modal-adaptive feature modulation and sparse transformer fusion
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DOI number:
10.1016/j.inffus.2025.103750
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Affiliation of Author(s):
Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan 430079, Peoples R China
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Journal:
INFORMATION FUSION
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Funded by:
This work is supported by the National Key Research and Development Program of China (Grant Nos. 202
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Key Words:
Multimodal image matching,Feature modulation,Sparse transformer fusion,Top-k selection
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Abstract:
Multimodal image matching is a fundamental task in geospatial analysis, aiming to establish accurate correspondences between images captured by heterogeneous imaging devices. However, significant geometric inconsistencies and nonlinear radiometric distortions lead to large distribution gaps, posing a major challenge for cross-modal matching. Moreover, existing methods often struggle to adaptively capture intra-and inter-modal features at multiple scales and to focus on semantically relevant regions in large-scale scenes. To address these issues, we propose a novel cross-modal image matching ne
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Co-author:
Pengcheng,Wei, Jindou,Zhang, Peilian, Jiayi,Ma, Liang,Wu, Mingqiang,Guo, Boshen,Chang
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Indexed by:
Journal paper
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Correspondence Author:
Zhenfeng,Shao
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Volume:
127
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ISSN No.:
1566-2535
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Translation or Not:
no
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Date of Publication:
2026-03-01
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