Guy Gilboa

Technion – Israel Institute of Technology

Papers

Total Citations

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About

Guy Gilboa is a leading researcher in computer vision and image processing, with a primary focus on depth sensing, signal recovery, and computational imaging. His work addresses critical challenges in autonomous navigation and robotics, particularly in developing algorithms that can robustly reconstruct depth information from heavily degraded or low-quality sensor data. In his 2016 paper, "Robust Recovery of Heavily Degraded Depth Measurements" (8 citations), Gilboa pioneered methods to salvage depth information from low-power, low-cost RGB-D sensors—a crucial advancement for mobile platforms and autonomous vehicles where power and price constraints are paramount. More recently, his 2020 work on "Super-Pixel Sampler: a Data-driven Approach for Depth Sampling and Reconstruction" (9 citations) introduced novel data-driven techniques for solid-state depth sensors, moving beyond traditional mechanical LiDAR systems. This work has significant implications for next-generation autonomous systems, offering more efficient and adaptive depth acquisition. Gilboa's research bridges the gap between theoretical signal processing and practical engineering constraints, making him a key figure in the development of robust, real-world depth sensing solutions for autonomous and robotic applications.