DEX: Deep EXpectation of Apparent Age from a Single Image
ETH Zurich · Board of the Swiss Federal Institutes of Technology
Abstract
In this paper we tackle the estimation of apparent age in still face images with deep learning. Our convolutional neural networks (CNNs) use the VGG-16 architecture [13] and are pretrained on ImageNet for image classification. In addition, due to the limited number of apparent age annotated images, we explore the benefit of finetuning over crawled Internet face images with available age. We crawled 0.5 million images of celebrities from IMDB and Wikipedia that we make public. This is the largest public dataset for age prediction to date. We pose the age regression problem as a deep classification problem followed by a softmax expected value refinement and show improvements over direct regression training of…
Citation impact
- FWCI
- 28.07
- Percentile
- 100%
- References
- 17
Authors
3Topics & keywords
- Softmax function
- Convolutional neural network
- Computer science
- Artificial intelligence
- Face (sociological concept)
- Deep learning
- Image (mathematics)
- Pattern recognition (psychology)
- Quality Education