arXiv:2606.04881v1 Announce Type: cross Abstract: Face aging plays an important role in long-term biometric analysis, cross-age identity verification, and forensic identity analysis. Since the same subject may exhibit multiple plausible appearances at a target age due to genetic, environmental, and lifestyle factors, face aging is inherently a one-to-many generation problem. However, pluralism alone is insufficient for reliable face aging: a model should provide appearance-level candidate diversity within each age group while maintaining sequence-level ordinal reliability across ordered age gr
Advances in generative AI models and computational power are enabling more sophisticated and reliable face manipulation research, necessary for applications like long-term biometrics.
This development enhances the reliability of face aging technology, crucial for security, forensic analysis, and personal identification across significant time spans despite inherent biological variations.
The ability to generate pluralistic yet reliable age progressions means facial recognition systems can become more robust against aging, leading to more secure and adaptable identity verification across time.
- · Biometric security firms
- · Law enforcement agencies
- · AI research and development
- · Forensic science
- · Criminals using aging to evade identification
- · Outdated facial recognition systems
Improved accuracy in identifying individuals over long periods, enhancing national security and criminal investigations.
Increased adoption of age-progression technologies in various sectors, leading to new ethical and privacy discussions.
The development of counter-technologies or regulations to manage the potential misuse of highly realistic and controllable face aging algorithms.
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Read at arXiv cs.AI