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Universal Spectral Adversarial Attacks for Deformable Shapes.

CVPR, pp.3216-3226, (2021)

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Abstract

Machine learning models are known to be vulnerable to adversarial attacks, namely perturbations of the data that lead to wrong predictions despite being imperceptible. However, the existence of "universal" attacks (i.e., unique perturbations that transfer across different data points) has only been demonstrated for images to date. Part ...More

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Author
Arianna Rampini
Arianna Rampini
Franco Pestarini
Franco Pestarini
Luca Cosmo
Luca Cosmo
Simone Melzi
Simone Melzi
Emanuele Rodolà
Emanuele Rodolà
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