Jiawei Zheng

Intelligent Systems Research (United States)

Papers

1

Total Citations

1

H-Index

1

About

Jiawei Zheng is a researcher at the forefront of computer vision and robotics, with a specialized focus on the challenging domain of transparent object perception. Their key research areas include semantic segmentation, transformer-based architectures, and robotic scene understanding. Zheng’s most notable contribution is the development of **TOSQ (Transparent Object Segmentation via Query-Based Dictionary Lookup with Transformers)**, a pioneering framework that addresses the long-standing difficulty of segmenting transparent objects in unpredictable environments. Unlike traditional methods that struggle with the lack of fixed visual patterns—such as reflections and background distortions—TOSQ leverages a query-based dictionary lookup mechanism within a transformer architecture to robustly identify transparent surfaces. This work, published in 2025, has already garnered attention for its potential to enhance robot navigation and grasping in human-centric spaces. While still early in its citation impact, the paper’s innovative approach to a notoriously hard problem positions Zheng as a rising authority in vision-based robotics. Their research directly bridges the gap between theoretical computer vision and practical, real-world applications, promising safer and more reliable autonomous systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
1
Total Citations
1
Avg Citations/Paper
🏆 Most Cited Paper
TOSQ: Transparent Object Segmentation via Query-Based Dictionary Lookup with Transformers
1 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Intelligent Systems Research (United States)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago