Attack: AutoAttack: 78.13
Papers with Code · CC BY-SA 4.0
Adversarial Attack
An Adversarial Attack is a technique to find a perturbation that changes the prediction of a machine learning model. The perturbation can be very small and imperceptible to human eyes.
<span class="description-source">Source: Recurrent Attention Model with Log-Polar Mapping is Robust against Adversarial Attacks </span>
논문
Attack: PGD20: 78.680Attack: DeepFool: 51.310Attack: AutoAttack: 44.150
Robust Accuracy: 1%
Attack: AutoAttack: 59.70
SDR: 0.70dB
Attack: PGD20: 45.900
Attack: PGD20: 48.440