论文标题
福斯：多人年龄估计，重点关注对象并仍然看到周围环境
FOSS: Multi-Person Age Estimation with Focusing on Objects and Still Seeing Surroundings
论文作者
论文摘要
来自图像的年龄估计可以在许多实际场景中使用。以前的大多数作品针对的是仅存在一个面孔的图像的估计。同样，大多数开放数据集用于年龄估计，包含类似的图像。但是，在某些情况下，需要野外和多人的年龄估计。通常，这种情况通过两个单独的模型解决。一种是面部探测器模型，该模型的面部区域，另一个是一个年龄估计模型，该模型是根据裁剪图像估算的。在这项工作中，我们提出了一种可以通过单个模型来检测和估计多人年龄的方法，该模型估算了年龄的关注面孔并仍然看到周围环境。另外，我们提出了一种训练方法，尽管对只有一张脸的图像进行了培训，但尽管训练了一张脸，但该方法可以很好地估算多人。在实验中，我们使用了两个单独的模型进行了与传统方法相比，我们评估了我们提出的方法。结果，我们提出的方法可以提高精度。我们还将提出的模型调整为常用的单人照片估计数据集，并证明我们的方法对这些图像也有效，并且胜过了最准确性的状态。
Age estimation from images can be used in many practical scenes. Most of the previous works targeted on the estimation from images in which only one face exists. Also, most of the open datasets for age estimation contain images like that. However, in some situations, age estimation in the wild and for multi-person is needed. Usually, such situations were solved by two separate models; one is a face detector model which crops facial regions and the other is an age estimation model which estimates from cropped images. In this work, we propose a method that can detect and estimate the age of multi-person with a single model which estimates age with focusing on faces and still seeing surroundings. Also, we propose a training method which enables the model to estimate multi-person well despite trained with images in which only one face is photographed. In the experiments, we evaluated our proposed method compared with the traditional approach using two separate models. As the result, the accuracy could be enhanced with our proposed method. We also adapted our proposed model to commonly used single person photographed age estimation datasets and it is proved that our method is also effective to those images and outperforms the state of the art accuracy.
