5 papers
PairedGTA: Generating Driving Datasets for Controlled Photometric Shift Analysis
Andrea Chianese, Giulio Rossolini, Alessandro Biondi +2
Evaluating the performance of visual perception systems for autonomous driving is essential to ensure reliable operation across diverse environmental scenarios. Ideally, a balanced…
Learning Robustness at Test-Time from a Non-Robust Teacher
Stefano Bianchettin, Giulio Rossolini, Giorgio Buttazzo
Nowadays, pretrained models are increasingly used as general-purpose backbones and adapted at test-time to downstream environments where target data are scarce and unlabeled. While…
Exploiting Edge Features for Transferable Adversarial Attacks in Distributed Machine Learning
Giulio Rossolini, Fabio Brau, Alessandro Biondi +2
As machine learning models become increasingly deployed across the edge of internet of things environments, a partitioned deep learning paradigm in which models are split across mu…
Video Deblurring by Sharpness Prior Detection and Edge Information
Yang Tian, Fabio Brau, Giulio Rossolini +2
Video deblurring is essential task for autonomous driving, facial recognition, and security surveillance. Traditional methods directly estimate motion blur kernels, often introduci…
1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness
Bernd Prach, Fabio Brau, Giorgio Buttazzo +1
The robustness of neural networks against input perturbations with bounded magnitude represents a serious concern in the deployment of deep learning models in safety-critical syste…