8 papers
Fast and Accurate Outlier-Aware LiDAR Super-Resolution for SLAM Applications
Christos Anagnostopoulos, Alexandros Gkillas, Nikos Piperigkos +1
This work tackles the challenge of enhancing low-resolution LiDAR sensors for SLAM applications through a novel Deep Unrolling-based Super-Resolution (SR) model. We integrate an ou…
Guided Model-based LiDAR Super-Resolution for Resource-Efficient Automotive scene Segmentation
Alexandros Gkillas, Nikos Piperigkos, Aris S. Lalos
High-resolution LiDAR data plays a critical role in 3D semantic segmentation for autonomous driving, but the high cost of advanced sensors limits large-scale deployment. In contras…
Integrated Simulation Framework for Adversarial Attacks on Autonomous Vehicles
Christos Anagnostopoulos, Ioulia Kapsali, Alexandros Gkillas +2
Autonomous vehicles (AVs) rely on complex perception and communication systems, making them vulnerable to adversarial attacks that can compromise safety. While simulation offers a…
Efficient Model-Based Purification Against Adversarial Attacks for LiDAR Segmentation
Alexandros Gkillas, Ioulia Kapsali, Nikos Piperigkos +1
LiDAR-based segmentation is essential for reliable perception in autonomous vehicles, yet modern segmentation networks are highly susceptible to adversarial attacks that can compro…
A holistic perception system of internal and external monitoring for ground autonomous vehicles: AutoTRUST paradigm
Alexandros Gkillas, Christos Anagnostopoulos, Nikos Piperigkos +16
This paper introduces a holistic perception system for internal and external monitoring of autonomous vehicles, with the aim of demonstrating a novel AI-leveraged self-adaptive fra…
Robustifying 3D Perception via Least-Squares Graphs for Multi-Agent Object Tracking
Maria Damanaki, Ioulia Kapsali, Nikos Piperigkos +2
The critical perception capabilities of EdgeAI systems, such as autonomous vehicles, are required to be resilient against adversarial threats, by enabling accurate identification a…