Stamatios Georgoulis
Papers
1
Total Citations
6
H-Index
1
About
Stamatios Georgoulis is a leading researcher in computer vision and autonomous systems, with a focus on enabling intelligent agents to perceive and predict their environments with high reliability. His key research areas include field-of-view extrapolation, uncertainty estimation, and self-attention mechanisms for scene understanding. Georgoulis is best known for his pioneering work on FoV-Net, a framework that leverages self-attention and uncertainty modeling to allow autonomous vehicles and robots to make educated predictions about their surroundings beyond their immediate sensor range. This capability is critical for early planning and decision-making in dynamic environments. His most cited paper, "FoV-Net: Field-of-View Extrapolation Using Self-Attention and Uncertainty" (2021), has garnered 6 citations, reflecting its growing influence in the field. Georgoulis’s contributions are particularly notable for bridging the gap between perception and prediction, providing intelligent systems with the confidence metrics needed to operate safely. His work is highly relevant to advancing autonomous navigation and robotics, where anticipating unseen obstacles or changes is essential.
Research Focus
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Top Papers
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