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arXiv · 2308.11896

Age Prediction From Face Images Via Contrastive Learning

Yeongnam Chae·Poulami Raha·Mijung Kim·Bjorn Stenger
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Abstract

This paper presents a novel approach for accurately estimating age from face images, which overcomes the challenge of collecting a large dataset of individuals with the same identity at different ages. Instead, we leverage readily available face datasets of different people at different ages and aim to extract age-related features using contrastive learning. Our method emphasizes these relevant features while suppressing identity-related features using a combination of cosine similarity and triplet margin losses. We demonstrate the effectiveness of our proposed approach by achieving state-of-the-art performance on two public datasets, FG-NET and MORPH-II.

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Yeongnam Chae, Poulami Raha, Mijung Kim, Bjorn Stenger. 2023-08-23. Age Prediction From Face Images Via Contrastive Learning. https://arxiv.org/abs/2308.11896

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