Real-World Adversarial Defense against Patch Attacks based on Diffusion Model
Adversarial patches present significant challenges to the robustness of deep learning models, making the development of effective defenses become critical for real-world applications. This paper introduces DIFFender, a novel DIFfusion-based DeFender framework that leverages the power of a text-guide...
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| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2025) vom: 06. Aug.
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| Auteur principal: |
Wei, Xingxing
(Auteur) |
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| Autres auteurs: |
Kang, Caixin,
Dong, Yinpeng,
Wang, Zhengyi,
Ruan, Shouwei,
Chen, Yubo,
Su, And Hang |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2025
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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