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Found 3 papers, 1 papers with code
On the reversibility of adversarial attacks
We refer to this property as the reversibility of an adversarial attack, and quantify reversibility as the accuracy in retrieving the original class or the true class of an adversarial example.
Underwater image filtering: methods, datasets and evaluation
The growing interest in underwater image filtering methods--including learning-based approaches used for both restoration and enhancement--and the associated challenges call for a comprehensive review of the state of the art.
Exploiting vulnerabilities of deep neural networks for privacy protection
To address these limitations, we present an adversarial attack {that is} specifically designed to protect visual content against { unseen} classifiers and known defenses.
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