Nazanin Padkan

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About

Nazanin Padkan is a researcher at the forefront of photogrammetry and computer vision, with a specialized focus on monocular depth estimation (MDE)—a critical technology for enabling machines to perceive three-dimensional space from a single RGB image. Her work addresses one of the field’s most challenging inverse problems: inferring accurate depth cues without the aid of stereo vision or LiDAR. Padkan’s most cited paper, “Evaluating Monocular Depth Estimation Methods” (2023), provides a systematic and rigorous benchmark of state-of-the-art MDE techniques, offering invaluable guidance for researchers and practitioners in simultaneous localization and mapping (SLAM), autonomous navigation, and augmented reality. This contribution has already garnered 6 citations, reflecting its timely relevance in a rapidly evolving domain. By critically assessing the strengths and limitations of existing algorithms, Padkan’s work helps bridge the gap between theoretical advances and practical deployment. Her research not only advances the fundamental understanding of depth perception but also supports the development of more robust, cost-effective vision systems. For students and researchers entering the field, Padkan’s evaluations serve as a foundational reference, illuminating both the promise and the persistent challenges of monocular depth estimation.