Deep Learning for Face Detection: Recent Advancements

Various applications like face analysis, recognition, reidentification exist where the use of Face Detection is necessary as their preprocessing algorithm in the pipeline. There has been extensive studies done in the domain of Face Detection in the past, and various robust algorithms have been proposed and evaluated on different datasets. Such techniques are also deployed in various applications. Although it may seem that this domain is very old and much work must have been done in it, there is still room for improvement. Previous studies have targeted issues like facial poses, expressions, scales of images and occlusions, and have achieved good accuracy. In recent years, work on advanced issues like low-resolution images, usage of proposed anchors, scale-invariance of models, minimization of model size, have been explored and various solutions have been proposed. In this paper, we will discuss the state-of-the-art publications in this domain, what issues they are targeting and what technologies they are using.