Yunzhe Li
Papers
1
Total Citations
5
H-Index
1
About
Yunzhe Li is a researcher advancing the frontiers of 3D computer vision, with a primary focus on monocular depth estimation and object detection for mobile platforms. Their most notable contribution is the development of a novel framework for mobile monocular 3D object detection that exploits ground depth estimation to overcome the inherent challenges of near-far disparity and dynamic camera motion. This work, published in 2025 and already garnering 5 citations, addresses a critical bottleneck in deploying accurate 3D perception on resource-constrained systems like vehicles, drones, and robots. By leveraging geometric priors from the ground plane, Li’s approach significantly improves detection accuracy for distant objects, a long-standing hurdle in the field. This innovation holds promise for enhancing autonomous navigation and augmented reality applications. Li’s research not only demonstrates technical rigor but also practical relevance, pushing the boundaries of what is achievable with monocular vision in real-world, mobile settings. Their work stands as a valuable resource for students and engineers seeking to bridge the gap between theoretical computer vision and deployable, high-performance systems.
Research Focus
Key Achievements
Top Papers
- 1