5 papers · 1 filter
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…
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…
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…
Optimizing Cooperative Multi-Object Tracking using Graph Signal Processing
Maria Damanaki, Nikos Piperigkos, Alexandros Gkillas +1
Multi-Object Tracking (MOT) plays a crucial role in autonomous driving systems, as it lays the foundations for advanced perception and precise path planning modules. Nonetheless, s…
Personalized Federated Learning for Cross-view Geo-localization
Christos Anagnostopoulos, Alexandros Gkillas, Nikos Piperigkos +1
In this paper we propose a methodology combining Federated Learning (FL) with Cross-view Image Geo-localization (CVGL) techniques. We address the challenges of data privacy and het…