Self-supervised Adversarial Training of Monocular Depth Estimation against Physical-World Attacks
Monocular Depth Estimation (MDE) plays a vital role in applications such as autonomous driving. However, various attacks target MDE models, with physical attacks posing significant threats to system security. Traditional adversarial training methods, which require ground-truth labels, are not direct...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2024) vom: 17. Juni
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| 1. Verfasser: |
Cheng, Zhiyuan
(VerfasserIn) |
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| Weitere Verfasser: |
Han, Cheng,
Liang, James,
Wang, Qifan,
Zhang, Xiangyu,
Liu, Dongfang |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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