4 papers
AD4AD: Benchmarking Visual Anomaly Detection Models for Safer Autonomous Driving
Fabrizio Genilotti, Arianna Stropeni, Gionata Grotto +4
The reliability of a machine vision system for autonomous driving depends heavily on its training data distribution. When a vehicle encounters significantly different conditions, s…
Efficient Visual Anomaly Detection at the Edge: Enabling Real-Time Industrial Inspection on Resource-Constrained Devices
Arianna Stropeni, Fabrizio Genilotti, Francesco Borsatti +3
Visual Anomaly Detection (VAD) is essential for industrial quality control, enabling automatic defect detection in manufacturing. In real production lines, VAD systems must satisfy…
Deep Learning for Virtual Reality User Identification: A Benchmark
Davide Frizzo, Fabrizio Genilotti, David Petrovic +6
Virtual Reality (VR) applications require robust user identification systems to ensure secure access to equipment and protect worker identities. Motion tracking data from VR headse…
VAD4Space: Visual Anomaly Detection for Planetary Surface Imagery
Fabrizio Genilotti, Arianna Stropeni, Francesco Borsatti +3
Space missions generate massive volumes of high-resolution orbital and surface imagery that far exceed the capacity for manual inspection. Detecting rare phenomena is scientificall…