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Age-Invariant Face Recognition

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

Age-invariant face recognition is the task of performing face recognition that is invariant to differences in age.

<span style="color:grey; opacity: 0.6">( Image credit: Look Across Elapse )</span>

데이터셋

출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.

MORPH is a facial age estimation dataset, which contains 55,134 facial images of 13,617 subjects ranging from 16 to 77 years old. Source: Deep Ordinal Regression Forests Image Source: https://uncw.edu/oic/tech/morph.html

FGNet is a dataset for age estimation and face recognition across ages. It is composed of a total of 1,002 images of 82 people with age range from 0 to 69 and an age gap up to 45 years Source: Large age-gap face verification by feature injection in deep networks Image Source: https://www.researchgate.net/figure/Sample-images-from-the-FG-NET-Aging-database_fig1_220057621

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