Open Access
Review
Table 1
Different surveys on adversarial examples
| Survey | Year | Venue | Attack? | Defense? | SOTA | Focus | Perspective | Highlights |
|---|---|---|---|---|---|---|---|---|
| Serban et al[14] | 2020 | CSUR | √ | √ | 2020 | Object Detection |
Neutral | Aware of earlier adversarial examples in machine learning |
| Machado et al[15] | 2021 | CSUR | √ | √ | 2021 | General CV |
Defender | Instructive for defense design |
| Long et al[16] | 2022 | C&S | √ | × | 2022 | General CV |
Attacker | Abundant visualization results |
| Wang et al[17] | 2022 | Neural Comput. | √ | √ | 2022 | General CV |
Neutral | Comprehensive taxonomy of attacks and defenses |
| Li et al[18] | 2024 | CSUR | √ | × | 2023 | 2D&3D CV |
Attacker | Considering 3D vision tasks |
| Costa et al[19] | 2024 | ACCESS | √ | √ | 2024 | General CV |
Neutral | Including SOTA performance; Considering transformers |
| Ours | 2024 | － | √ | √ | 2024 | General CV |
Neutral | Discussing critical issues beyond attack and defense |
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