Yong Jae Lee
Papers
1
Total Citations
60
H-Index
1
About
Yong Jae Lee is a leading researcher in computer vision and machine learning, with a focus on privacy-preserving technologies and generative models. His most notable contribution is the development of **Password-Conditioned Anonymization and Deanonymization with Face Identity Transformers**, a 2020 paper that has garnered 60 citations. This work introduces a novel framework for reversible face anonymization, allowing users to control identity masking with a password—enabling both privacy protection and authorized identity recovery. Lee’s research addresses critical challenges in balancing visual data utility with individual privacy, particularly in surveillance and social media applications. His work has been recognized for its practical impact, bridging gaps between security, ethics, and AI. By pioneering methods that transform facial features while preserving semantic context, Lee has influenced subsequent studies in adversarial privacy and identity obfuscation. His contributions are essential for students and researchers exploring ethical AI, data anonymity, and the societal implications of computer vision systems.
Research Focus
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Top Papers
- 1