From Cradle to Cane: ATwo-Pass Framework for High-Fidelity Lifespan Face Aging

Neural Information Processing Systems 

Face aging has become a crucial task in computer vision, with applications ranging from entertainment to healthcare. However, existing methods struggle with achieving a realistic and seamless transformation across the entire lifespan, especially when handling large age gaps or extreme head poses. The core challenge lies in balancing age accuracy and identity preservation--what we refer to as the Age-ID trade-off.

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