most citedExploiting vulnerabilities of deep neural networks for privacy protection

25 citations · 36 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022

On the limits of perceptual quality measures for enhanced underwater images

Chau Yi Li, Andrea Cavallaro

The appearance of objects in underwater images is degraded by the selective attenuation of light, which reduces contrast and causes a colour cast. This degradation depends on the w…

cs.LG2022

On the reversibility of adversarial attacks

Chau Yi Li, Ricardo Sánchez-Matilla, Ali Shahin Shamsabadi +2

Adversarial attacks modify images with perturbations that change the prediction of classifiers. These modified images, known as adversarial examples, expose the vulnerabilities of…

cs.CV2022

Training privacy-preserving video analytics pipelines by suppressing features that reveal information about private attributes

Chau Yi Li, Andrea Cavallaro

Deep neural networks are increasingly deployed for scene analytics, including to evaluate the attention and reaction of people exposed to out-of-home advertisements. However, the f…

cs.CV2020★ 11 cited

Underwater image filtering: methods, datasets and evaluation

Chau Yi Li, Riccardo Mazzon, Andrea Cavallaro

Underwater images are degraded by the selective attenuation of light that distorts colours and reduces contrast. The degradation extent depends on the water type, the distance betw…

cs.CV2020★ 25 cited

Exploiting vulnerabilities of deep neural networks for privacy protection

Ricardo Sanchez-Matilla, Chau Yi Li, Ali Shahin Shamsabadi +2

Adversarial perturbations can be added to images to protect their content from unwanted inferences. These perturbations may, however, be ineffective against classifiers that were n…