5 papers · 1 filter
Adversarial Decoys: Misdirecting Attention-Based Defenses in ViT
Giulia Marchiori Pietrosanti, Giulio Rossolini, Giorgio Buttazzo
Vision Transformers (ViTs) remain vulnerable to localized adversarial attacks, e.g., adversarial patches, while recent test-time defenses mitigate them by suppressing image tokens…
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…
Benchmarking the Spatial Robustness of DNNs via Natural and Adversarial Localized Corruptions
Giulia Marchiori Pietrosanti, Giulio Rossolini, Alessandro Biondi +1
The robustness of deep neural networks is a crucial factor in safety-critical applications, particularly in complex and dynamic environments (e.g., medical or driving scenarios) wh…
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…