AI RESEARCH

DiverAge: Reliable Pluralistic Face Aging with Cross-Age Identity Relation Guidance

arXiv CS.AI

ArXi:2606.04881v1 Announce Type: cross 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 groups.