Xuanyang Zhang
Papers
2
Total Citations
12
H-Index
2
About
Xuanyang Zhang is a researcher at the forefront of computer vision, with a focused expertise in egocentric perception and 3D hand-object interaction modeling. His work addresses a critical challenge: enabling machines to understand how humans naturally use their hands to interact with the world from a first-person perspective. Zhang’s major contribution is the development of comprehensive benchmarks and frameworks for pose estimation in egocentric hand interactions with objects. His highly cited 2024 paper on this topic (garnering 10 citations) systematically defines the challenges and evaluation protocols for reconstructing holistic 3D interactions, which is foundational for advancing applications in robotics, augmented and virtual reality (AR/VR), action recognition, and motion generation. By providing standardized datasets and rigorous baselines, Zhang has helped bridge the gap between raw egocentric video and actionable 3D understanding. His work is instrumental in pushing the boundaries of how AI systems perceive and interpret dexterous human manipulation, making him a key contributor to the next generation of immersive and interactive technologies.
Research Focus
Key Achievements
Top Papers
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