Yumei Chai
Papers
1
Total Citations
10
H-Index
1
About
Yumei Chai is a computer vision researcher whose work centers on advancing object tracking and visual understanding in unconstrained environments. Her most notable contribution, the "Planar object tracking benchmark in the wild" (2021), has garnered 10 citations and addresses a critical gap in the field by providing a standardized evaluation framework for tracking planar surfaces under real-world conditions—such as varying lighting, occlusion, and perspective changes. This benchmark has become a valuable resource for researchers developing robust tracking algorithms, particularly for augmented reality and robotics applications. Chai’s work demonstrates a keen focus on bridging the gap between controlled laboratory settings and practical deployment, ensuring that tracking systems perform reliably in dynamic, unpredictable scenes. Her contributions highlight the importance of rigorous benchmarking in driving reproducible progress, and her research continues to influence the development of more adaptive and resilient visual tracking methods.
Research Focus
Key Achievements
Top Papers
- 1Planar object tracking benchmark in the wild10 citations · 2021