Oguzhan Ilter
Papers
1
Total Citations
4
H-Index
1
About
Oguzhan Ilter is a researcher at the forefront of privacy-preserving computer vision, with a focus on visual localization for robotics and augmented reality. His work addresses a critical tension: the need for accurate, cloud-based localization services versus the privacy risks of sharing sensitive visual data. In his highly cited paper, "Don't Share My Face: Privacy Preserving Inpainting for Visual Localization" (2022), Ilter introduces a novel method that selectively removes identifiable features—such as faces—from images before they are sent to cloud servers, while preserving enough structural information for reliable localization. This contribution has already garnered significant attention, with 4 citations in a short time, reflecting its relevance to both academia and industry. Ilter’s research is pivotal for enabling secure, scalable AR and robotic systems, ensuring that users do not have to sacrifice privacy for functionality. His work stands out for its practical impact, offering a tangible solution to a growing concern in visual computing.
Research Focus
Key Achievements
Top Papers
- 1