activity
20192021
most citedTowards robust sensing for Autonomous Vehicles: An adversarial perspective

50 citations · 75 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Improving filling level classification with adversarial training

Apostolos Modas, Alessio Xompero, Ricardo Sanchez-Matilla +2

We investigate the problem of classifying - from a single image - the level of content in a cup or a drinking glass. This problem is made challenging by several ambiguities caused…

cs.CV202025 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…

eess.SP202050 cited

Towards robust sensing for Autonomous Vehicles: An adversarial perspective

Apostolos Modas, Ricardo Sanchez-Matilla, Pascal Frossard +1

Autonomous Vehicles rely on accurate and robust sensor observations for safety critical decision-making in a variety of conditions. Fundamental building blocks of such systems are…

cs.CV2019

Multi-view shape estimation of transparent containers

Alessio Xompero, Ricardo Sanchez-Matilla, Apostolos Modas +2

The 3D localisation of an object and the estimation of its properties, such as shape and dimensions, are challenging under varying degrees of transparency and lighting conditions.…

cs.CV2019

ColorFool: Semantic Adversarial Colorization

Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Andrea Cavallaro

Adversarial attacks that generate small L_p-norm perturbations to mislead classifiers have limited success in black-box settings and with unseen classifiers. These attacks are also…