Yuwei Zeng
Papers
2
Total Citations
13
H-Index
2
About
Yuwei Zeng is a researcher advancing the intersection of computer vision, robotics, and 3D modeling, with a focused expertise in garment and deformable object manipulation. Their most notable contribution is the creation of **ClothesNet**, an information-rich 3D garment model repository and simulated clothes environment. This large-scale dataset comprises approximately 4,400 models across 11 categories, each meticulously annotated with clothes features, boundary lines, and keypoints. By providing this richly structured data, Zeng’s work directly addresses a critical bottleneck in robotic cloth handling and garment simulation, enabling more robust perception and manipulation algorithms. With over 13 citations for this single work, ClothesNet has quickly become a foundational resource for researchers tackling the challenges of deformable object interaction. Zeng’s contributions are particularly impactful for students and researchers in embodied AI, where realistic, annotated assets are essential for training and evaluating systems. Through ClothesNet, Yuwei Zeng has established a vital benchmark that accelerates progress in garment modeling and robotic cloth manipulation, bridging the gap between synthetic data and real-world application.
Research Focus
Key Achievements
Top Papers
- 1
- 2