7 papers · 1 filter
Adversarially Guided Diffusion for LiDAR Range Image Synthesis
Stavros Bouras, Antonios Makris, Alexandros Gkillas +2
LiDAR semantic segmentation is a key perception task in autonomous driving, where false predictions can affect downstream planning and safety-critical decision-making. Although adv…
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…
A Deep Unrolling Model with Hybrid Optimization Structure for Hyperspectral Image Deconvolution
Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis
In recent literature there are plenty of works that combine handcrafted and learnable regularizers to solve inverse imaging problems. While this hybrid approach has demonstrated pr…