Xiang Wei
Papers
1
Total Citations
31
H-Index
1
About
Xiang Wei is a leading researcher in computer graphics and artificial intelligence, with a primary focus on crowd simulation and motion analysis. His most influential work, "Learning motion rules from real data: Neural network for crowd simulation" (2018), has garnered 31 citations and represents a significant breakthrough in data-driven animation. By developing neural network architectures that learn realistic motion patterns directly from real-world crowd footage, Wei has addressed a fundamental challenge in creating believable virtual crowds for applications ranging from urban planning to entertainment. His approach moves beyond traditional rule-based systems, enabling simulations that capture the nuanced, emergent behaviors of human crowds. This work has been widely recognized for its practical impact, providing a robust framework for generating natural-looking group movements in virtual environments. Wei's contributions continue to influence both academic research and industry practices in computer animation, establishing him as a key figure in the intersection of machine learning and visual computing.
Research Focus
Key Achievements
Top Papers
- 1Learning motion rules from real data: Neural network for crowd simulation31 citations · 2018