Xu-Cheng Yin
Papers
2
Total Citations
33
H-Index
2
About
Xu-Cheng Yin is a leading researcher in computer vision and multimedia content analysis, with a primary focus on scene text detection and optical flow estimation. His pioneering work on video text detection, particularly the influential paper "Scene text detection in video by learning locally and globally" (2016, 22 citations), addressed the grand challenges of extracting text from complex video environments with heterogeneous backgrounds, varied fonts, and nonuniform illumination. By integrating both local and global learning strategies, Yin's approach significantly advanced the robustness of text extraction in real-world robotic and user applications. More recently, he has made substantial contributions to efficient motion estimation with the development of RAPIDFlow (2024, 11 citations), a recurrent adaptable pyramid framework with iterative decoding that achieves high accuracy in optical flow while being computationally efficient enough for embedded devices. This work directly addresses the critical need for real-time motion analysis in robotics and autonomous systems. With over 33 citations across his most recognized works, Yin's research continues to bridge the gap between theoretical computer vision and practical deployment, making him a notable figure in the field of video analysis and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1Scene text detection in video by learning locally and globally22 citations · 2016
- 2