Few Shot Age Estimation

Few-shot Age Estimation is a subtask in the field of computer vision that focuses on accurately estimating the age of individuals across different age groups with extremely limited samples (such as 1, 2, 4, 8, 16, 32, or 64). The goal of this task is to enable efficient learning through minimal data, enhancing the model's generalization capability on small datasets. This has broad application value in scenarios such as identity verification, personalized recommendations, and intelligent surveillance.