# Deep Convolutional Neural Network for Age Estimation based on VGG-Face Model

arXiv: https://arxiv.org/abs/1709.01664 · HTML: https://mlsanity.com/paper/1709.01664/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Sep 2017.

## Built on by (most cited first, 11 of 11)

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- [Realistic Speech-to-Face Generation with Speech-Conditioned Latent Diffusion Model with Face Prior](https://mlsanity.com/paper/2310.03363/) (2023)
- [2D-3D Attention and Entropy for Pose Robust 2D Facial Recognition](https://mlsanity.com/paper/2505.09073/) (2025)
- [Impact of Image Resolution on Age Estimation with DeepFace and InsightFace](https://mlsanity.com/paper/2511.14689/) (2025)
- [Age Range Estimation using MTCNN and VGG-Face Model](https://mlsanity.com/paper/2104.08585/) (2021)
- [ArcFace Knows the Gender, Too!](https://mlsanity.com/paper/2112.10101/) (2021)
- [MagicEye: An Intelligent Wearable Towards Independent Living of Visually Impaired](https://mlsanity.com/paper/2303.13863/) (2023)
- [7ABAW-Compound Expression Recognition via Curriculum Learning](https://mlsanity.com/paper/2503.07969/) (2025)
- [See the Speaker: Crafting High-Resolution Talking Faces from Speech with Prior Guidance and Region Refinement](https://mlsanity.com/paper/2510.26819/) (2025)

## Abstract (arXiv)

Automatic age estimation from real-world and unconstrained face images is rapidly gaining importance. In our proposed work, a deep CNN model that was trained on a database for face recognition task is used to estimate the age information on the Adience database. This paper has three significant contributions in this field. (1) This work proves that a CNN model, which was trained for face recognition task, can be utilized for age estimation to improve performance; (2) Over fitting problem can be overcome by employing a pretrained CNN on a large database for face recognition task; (3) Not only the number of training images and the number subjects in a training database effect the performance of the age estimation model, but also the pre-training task of the employed CNN determines the performance of the model.