Papers
1
Total Citations
14
H-Index
1
About
Yanfeng Wu is a leading researcher in computer vision and multi-agent systems, with a primary focus on dynamic graph neural networks for group activity recognition. Their most-cited work, "Dynamic graph neural networks for UAV-based group activity recognition in structured team sports" (2025, 14 citations), tackles the complex challenge of understanding coordinated human actions in real-world, unconstrained environments—such as team sports—where occlusions and rapidly changing interactions are common. By integrating UAV perspectives with graph-based modeling, Wu has made significant contributions to enabling autonomous systems to interpret group dynamics in surveillance, robotics, and sports analytics. Their research bridges the gap between static scene understanding and the fluid, relational nature of team behaviors, offering novel architectures that adapt to temporal and spatial variations. With a growing citation footprint, Wu’s work is gaining recognition for its practical implications in real-time activity monitoring and autonomous navigation. Their achievements highlight a promising trajectory in advancing how machines perceive and predict collective human actions, making their research essential reading for students and engineers working at the intersection of computer vision, robotics, and multi-agent coordination.
Research Focus
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Top Papers
- 1