Bingda Tang
Papers
1
Total Citations
3
H-Index
1
About
Bingda Tang is a rising researcher in computer vision and embodied AI, with a focus on understanding complex human-object and human-human interactions in 3D and 4D spaces. His key research areas include human-object interaction modeling, collaborative behavior analysis, and the creation of large-scale datasets for virtual and augmented reality applications. Tang’s most notable contribution is the introduction of **CORE4D**, a pioneering large-scale 4D dataset that captures human-object-human interactions during cooperative object rearrangement tasks. This work addresses a critical gap in the field, as prior datasets largely overlooked the dynamics of multi-person collaboration. By providing richly annotated spatiotemporal data, CORE4D enables advances in human-robot collaboration, VR/AR systems, and social activity understanding. Though early in its release, the dataset has already garnered attention, with 3 citations, and is poised to become a foundational resource for the community. Tang’s work exemplifies the shift from single-person action recognition to modeling realistic, multi-agent interactions—a vital step toward more intelligent and socially aware AI systems.
Research Focus
Key Achievements
Top Papers
- 1