Shanbao Qiao
Papers
1
Total Citations
10
H-Index
1
About
Shanbao Qiao is a leading researcher in computer vision and human-computer interaction, with a primary focus on 3D perception and self-supervised learning. His most cited work, "Self-Supervised Learning of Depth and Ego-Motion for 3D Perception in Human Computer Interaction" (2023, 10 citations), tackles a critical challenge in intelligent systems: enabling accurate 3D depth and ego-motion estimation without costly LiDAR sensors. By developing self-supervised methods that learn from unlabeled video data, Qiao has advanced affordable, scalable solutions for robotics and autonomous driving. His contributions are particularly impactful in human-computer interaction, where real-time 3D understanding is essential for natural user interfaces and safe autonomous navigation. Qiao’s research bridges the gap between theoretical machine learning and practical deployment, addressing the sensor cost barrier that limits widespread adoption of 3D perception. His work has been recognized for its potential to democratize access to advanced perception technologies, making him a notable figure in the intersection of computer vision and interactive systems.
Research Focus
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Top Papers
- 1