Minh Vo
Papers
1
Total Citations
29
H-Index
1
About
Minh Vo is a leading researcher in 3D computer vision, with a focus on scene understanding, object detection, and mapping for augmented reality and robotics. His most cited work, "ODAM: Object Detection, Association, and Mapping using Posed RGB Video" (2021, 29 citations), introduces a pioneering system that jointly localizes objects and estimates their 3D extent from posed RGB video streams. This contribution directly addresses a critical bottleneck in high-level 3D scene understanding—enabling machines to not only detect objects but also associate them across frames and build consistent object-level maps. By integrating detection, association, and mapping into a unified pipeline, Vo’s work has practical implications for autonomous navigation and AR, where spatial reasoning about objects is essential. His research stands out for its end-to-end approach, bridging low-level perception with semantic mapping. With growing citation impact, Minh Vo is establishing himself as a key contributor to the next generation of intelligent spatial perception systems.
Research Focus
Key Achievements
Top Papers
- 1ODAM: Object Detection, Association, and Mapping using Posed RGB Video29 citations · 2021