Papers

2

Total Citations

63

H-Index

2

About

Xiuye Gu is a researcher at the forefront of privacy-preserving computer vision, with a primary focus on developing technologies that balance the utility of visual data with the imperative of individual privacy. Her most significant contribution is the introduction of "Password-Conditioned Anonymization and Deanonymization with Face Identity Transformers," a groundbreaking framework that allows for the reversible anonymization of facial identities in images and videos. This work, published in 2020 and garnering 60 citations, directly addresses the growing societal concern over ubiquitous cameras in smart homes and service robots. By enabling a user to control the de-anonymization process with a password, Gu’s research offers a practical solution for systems that require both privacy protection and the ability to later verify identity, a critical step forward from irreversible blurring or masking techniques. Her work is notable for its innovative use of generative models to transform facial features while preserving other visual information, marking a key achievement in the emerging field of privacy-enhancing technologies for computer vision.

Research Focus

Key Achievements

2
H-Index
2
Papers
63
Total Citations
32
Avg Citations/Paper
🏆 Most Cited Paper
Password-Conditioned Anonymization and Deanonymization with Face Identity Transformers
60 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of California, Davis, Stanford University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago