Guanci Yang

Guizhou University

Papers

16

Total Citations

511

H-Index

10

About

Guanci Yang is a prominent researcher whose work bridges social robotics, computer vision, and smart home technologies, with a particular focus on improving the safety, privacy, and autonomy of robotic systems for elderly and disabled care. His research has made significant strides in several interconnected domains, including simultaneous localization and mapping (SLAM), face de-identification, and dietary health monitoring. Among his most influential contributions is his 2020 work on FPGAN, a generative adversarial network-based face de-identification method for social robots, which has garnered 135 citations and addresses critical privacy concerns in home environments. His improved ORB-SLAM2 algorithm for rapid mobile robot relocation (125 citations) has similarly shaped the field of real-time robotic navigation. Yang's sustained attention to privacy in smart homes is evident across multiple papers, including early work detecting embarrassing situations using convolutional neural networks (44 citations). More recently, his research has expanded into multi-object tracking and human-object interaction detection, reflecting an evolving and forward-looking research agenda. Collectively, his publications demonstrate a cohesive vision: enabling socially aware, privacy-respecting robots capable of meaningfully supporting human wellbeing in everyday environments.

Research Focus

Key Achievements

10
H-Index
16
Papers
511
Total Citations
32
Avg Citations/Paper
🏆 Most Cited Paper
FPGAN: Face de-identification method with generative adversarial networks for social robots
135 citations · 2020
📈 Most Prolific Year: 2018 (5 Papers)
🤝 Key Collaborators: 30
🏛 Institutions: Guizhou University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago