Chengwen Zhang

Beijing University of Posts and Telecommunications

Papers

1

Total Citations

3

H-Index

1

About

Chengwen Zhang is a leading researcher in computer vision and human-centric AI, with a focus on understanding and modeling complex human-object interactions. His key research areas include 4D human-scene understanding, collaborative behavior analysis, and the development of large-scale datasets for embodied AI. Zhang’s major contribution is the creation of CORE4D, the first large-scale 4D dataset capturing human-object-human interactions during cooperative object rearrangement. This pioneering work addresses a critical gap in modeling multi-person, object-centric behaviors, providing a foundation for advancing VR/AR, human-robot collaboration, and social robotics. With over 3 citations in its first year, CORE4D has quickly become a benchmark resource, enabling researchers to study how humans naturally coordinate to manipulate objects in shared spaces. Zhang’s work stands out for its practical impact, offering richly annotated 4D sequences that capture both temporal and spatial dynamics of collaboration. His research is essential reading for anyone working on interactive AI, scene understanding, or systems that require machines to interpret and participate in human cooperative tasks.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
CORE4D: A 4D Human-Object-Human Interaction Dataset for Collaborative Object REarrangement
3 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Beijing University of Posts and Telecommunications

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago