Academic Journal
SDCA: Towards semantic-guided dual camouflage for deceiving human eyes and object detectors.
| Τίτλος: | SDCA: Towards semantic-guided dual camouflage for deceiving human eyes and object detectors. |
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| Συγγραφείς: | Yuan H; School of Cyber Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, 210044, China., Chen X; School of Cyber Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Yuchi Blockchain Technology Research Institute Co., Ltd., Nanjing, 210018, China; Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, 210044, China. Electronic address: xianyi_chen@nuist.edu.cn., Cui Q; School of Cyber Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, 210044, China., Liu F; School of Cyber Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, 210044, China., Fu Z; School of Cyber Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, 210044, China. |
| Πηγή: | Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2026 Sep; Vol. 201, pp. 108946. Date of Electronic Publication: 2026 Apr 11. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Pergamon Press Country of Publication: United States NLM ID: 8805018 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-2782 (Electronic) Linking ISSN: 08936080 NLM ISO Abbreviation: Neural Netw Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: New York : Pergamon Press, [c1988- |
| Ιατρικοί όροι (MeSH): | Detection Algorithms* , Semantics*, Humans |
| Περίληψη: | Adversarial camouflage has gained widespread attention for its ability to prevent object detectors from accurately identifying physical-world targets. However, existing methods typically initialize textures with random values and exclude perturbation constraints during optimization. This approach lacks explicit guidance for generating perturbation patterns that conform to natural texture semantics (e.g., color distributions and contour structures), making the perturbations easily detected by biological vision systems. Regarding these problems, we propose Semantic-guided Dual Camouflage Attack (SDCA) from the perspective of joint optimization of natural semantics and adversarial perturbations. The core of SDCA consists of the Semantic-Driven Generator (SDG) and the Semantic-Constrained Optimization (SCO) strategy. SDG uses procedural noise to inversely model visual features of natural textures to achieve semantically-driven texture initialization. Meanwhile, SCO constrains the perturbation based on prior semantic information, preserving semantic consistency between the adversarial texture and the initial texture. Ultimately, SDCA can generate highly natural camouflage textures, achieving dual evasion of both biological vision systems and computer vision models. Experimental results on various detection tasks show that SDCA outperforms existing works in terms of naturalness while maintaining competitive robustness and transferability. The datasets and visualizations of SDCA are available at: https://github.com/Haoq1nYuan/Semantic-guided-Dual-Camouflage-Attack. (Copyright © 2026 Elsevier Ltd. All rights reserved.) |
| Competing Interests: | Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Contributed Indexing: | Keywords: Adversarial attack; Camouflage; Object detection; Perlin noise |
| Entry Date(s): | Date Created: 20260417 Date Completed: 20260613 Latest Revision: 20260619 |
| Update Code: | 20260620 |
| DOI: | 10.1016/j.neunet.2026.108946 |
| PMID: | 41996886 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1879-2782 |
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| DOI: | 10.1016/j.neunet.2026.108946 |