Linlin Yang
Papers
2
Total Citations
12
H-Index
2
About
Linlin Yang is a leading researcher in computer vision, with a primary focus on egocentric perception, hand-object interaction modeling, and 3D pose estimation. Her work addresses the fundamental challenge of understanding how humans interact with the world from a first-person viewpoint—a critical capability for advancing robotics, augmented and virtual reality (AR/VR), and action recognition. Yang’s most notable contribution is her comprehensive benchmark study on pose estimation for egocentric hand interactions with objects, which has garnered over 10 citations shortly after its 2024 publication. This work systematically evaluates the difficulties in reconstructing holistic 3D hand and object poses from egocentric video, providing standardized datasets and evaluation protocols that have become essential resources for the field. By highlighting the unique challenges of occlusions, rapid motion, and perspective distortion inherent to first-person views, Yang’s research pushes the boundaries of accurate 3D reconstruction. Her benchmarks serve as a foundation for future work in motion generation and interactive systems, making her a key figure in bridging computer vision and practical human-computer interaction.
Research Focus
Key Achievements
Top Papers
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- 2