Dean Diepeveen
Papers
1
Total Citations
55
H-Index
1
About
Dean Diepeveen is an emerging researcher whose work sits at the intersection of computer vision, deep learning, and spatial perception. His most notable contribution to date is a comprehensive 2024 survey on deep learning-based depth estimation from monocular images and videos, which has already accumulated 55 citations — a remarkable achievement for a recently published work. This survey synthesizes over a decade of progress across more than 500 deep learning publications, providing the research community with an authoritative reference covering applications spanning autonomous driving, 3D reconstruction, digital entertainment, and robotics. By systematically organizing and evaluating the rapid advances in monocular depth estimation — a challenging problem given the inherently ill-posed nature of inferring three-dimensional structure from a single camera — Diepeveen has made a significant service contribution to the field. His ability to distill a vast and fast-moving literature into accessible, structured insight reflects both breadth of knowledge and a talent for synthesis. Researchers and students entering the depth estimation space frequently turn to this work as a foundational starting point, underscoring its growing influence in the computer vision community.
Research Focus
Key Achievements
Top Papers
- 1