De-Qin Gao
Papers
1
Total Citations
16
H-Index
1
About
Dr. De-Qin Gao is a researcher in computer vision and autonomous driving, with a focus on cost-effective 3D perception systems. His most-cited work, "3D Object Detection Based on Proposal Generation Network Utilizing Monocular Images" (2021, 16 citations), addresses a critical challenge in autonomous vehicles and robotics: performing accurate 3D object detection using only a single camera. This approach offers a low-cost alternative to expensive LiDAR and stereo camera setups, making advanced perception more accessible. By developing a proposal generation network that extracts depth and spatial cues from monocular images, Gao’s research helps bridge the gap between affordability and performance in real-world navigation systems. His contributions are particularly relevant for applications where sensor budgets are limited, yet reliable 3D understanding is essential. With growing interest in monocular 3D detection, Gao’s work continues to influence the development of efficient, scalable perception pipelines for autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1