Marc Khoury
Papers
1
Total Citations
18
H-Index
1
About
Marc Khoury is a researcher whose work lies at the intersection of 3D vision, robotics, and geometric deep learning. He is best known for his pioneering contributions to learning compact geometric features from unstructured point clouds—a fundamental challenge for tasks like point cloud registration and 3D object recognition. His most-cited paper, "Learning Compact Geometric Features" (2017), introduced a novel approach for extracting local geometric descriptors directly from raw point cloud data, enabling more robust and efficient alignment of 3D scans. This work has garnered 18 citations and laid important groundwork for subsequent advances in learned 3D feature representations. Khoury’s research has direct applications in autonomous navigation, SLAM, and augmented reality, where accurate geometric registration is critical. By bridging classical geometry with modern learning techniques, he has helped shape how robots and autonomous systems perceive and interact with their 3D environments. His contributions continue to influence both academic research and practical deployment in real-world robotics and 3D vision systems.
Research Focus
Key Achievements
Top Papers
- 1Learning Compact Geometric Features18 citations · 2017